What You’ll Be Doing:

Work with product and program management in planning and execution of new product releases.

Translate high level customer needs into detailed technical requirements.

Work with engineering and core infrastructure teams on technical architecture, API design, usage dashboards, security and enterprise readiness.

Fully own the developer experience. BioNeMo microservices should be a delight to use for a drug discovery AI developer!

Partner with UX teams in defining the end-to-end user journey from feature discovery to commercial adoption.

Work with customers to collect technical feedback and use it to drive future roadmap.

Stay abreast of the latest developments in generative AI and drive product roadmap to incorporate latest SOTA AI models & techniques in anticipation of widespread adoption.

Work with Technical Marketing teams on demos and product marketing teams on product positioning and messaging.

Perform technical competitive analysis of other offerings in the market.

Support partners looking to use BioNeMo as a platform for distributing their AI models to end customers in BioPharma and Support early adopters through Early Access programs.

What We Need To See:

Bachelor's Degree in a quantitative field (e.g., Computer Science, Applied Math, Computational Science, Machine Learning, etc.) or equivalent experience.

Deep expertise and 5+ years hands on experience in cloud-native technologies on public cloud infrastructure (Docker containers, Kubernetes, service-oriented architecture).

Hands-on experience building AI models using Deep Learning frameworks like PyTorch, JAX, and DeepSpeed.

Excellent balance of deep technical and business knowledge of the cloud services space.

Analytical approach and ability to synthesize latest research, engineering feasibility, and market trends into product strategy.

World-class communication skills with a proven ability to articulate a value proposition to technical and non-technical audiences.

Work cross functionally with engineering, research, developer relations, and go to market teams.

Ability to manage concurrent projects and priorities in a dynamic environment.

Ways To Stand Out From The Crowd:

Hands on experience in AI Drug Discovery.

Prior product management experience in cloud services products.

Experience collaborating with and contributing to open-source projects.

Strong programming skills and familiarity with CUDA and GPU fundamentals.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant, forward-thinking and hardworking people in the world working for us. There has never been a more exciting time to join!

The base salary range is 132,000 USD - 247,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Research Scientist (Computational Biology), London
Isomorphic Labs is a new Alphabet company that is reimagining drug discovery through a computational- and AI-first approach.

We are on a mission to accelerate the speed, increase the efficacy and lower the cost of drug discovery. You'll be working at the cutting edge of the new era of 'digital biology' to deliver a transformative social impact for the benefit of millions of people.

Come and be part of a multi-disciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring, collaborative and entrepreneurial culture.

Your impact
This is an exciting opportunity for you to contribute to an ambitious Computational Biology research programme, working in partnership with leading ML researchers, Chemists and Biological Scientists. Building on the successful models in place to predict protein structure (AlphaFold-latest), there is an unique opportunity for an applied Research Scientist to have a direct impact on drug discovery, using innovative Computational Biology approaches. This is a newly created role; driven by a passion for problem solving, you will need to use your previous experience and show initiative in order to fully carve out your contribution.

What you will do
Partner with Isomorphic Labs Drug Discovery teams and wider organisation, to use pioneering Computational Biology methods to drive data enabled drug development
Develop and apply Computational Biology workflows to address common drug development research questions, spanning from target identification to clinical biomarker strategies
Use your shown experience of computational biology datasets, spanning statistical genetics, genomics, transcriptomics, proteomics, functional perturbation screens, imaging, knowledge graphs, PPI, clinical and other data types, to devise relevant computational experiments
Use data to drive biological insights and contribute to drug discovery programmes, becoming an integral member of project teams
Work in partnership with the Computational Biology research team members to evaluate experimental models under development and benchmark to existing methodologies
Work with Bioinformatics, Data and other groups to influence Iso’s datasets and pipelines strategy, ensuring innovative insights are consistently brought to bear within drug development programmes
Perform thorough data analysis and data quality assurance checks, with a strong focus on accuracy and reproducibility, inline with industry standard processes.
Contribute to the wider development of Iso’s ML computational platform, working with other engineers to architect, build and operate the platform’s components
Work with other members of the Computational Biology team to deliver a unified team strategy
Provide documentation, guidance and communication on computational biology to the wider organisation.
Skills and qualifications
Essential:
Experience in computational biology, with PhD and/or extensive experience
Expertise with detailed data quality control procedures and data visualisation
Solid experience with experimental design and statistical analysis
Solid understanding of computational biology tools and methodologies and experience with the analysis of large -omics datasets
Demonstrated understanding of the principles of molecular cell biology and genetics, or related biological disciplines
Familiarity with data processing pipelines and tools
Track record of using computational methods to gain novel biological insight
Ability to effectively communicate scientific concepts to a variety of audiences
Programming skills in a language such as Python (ideally), or R
Experience using common database platforms (e.g. BigQuery), and data integration approaches
Some exposure to cloud environments
Demonstrate ongoing career progression / trajectory and a passion for learning
Nice to have:
Post PhD research experience (i.e. some postdoctoral or industry experience)
Prior experience in the context of therapeutic or diagnostic development programmes
Familiarity with a variety of assaying techniques, including NGS, cell-based assays, functional genomics, single-cell techniques, and image-based assays with expertise in their respective data analysis approaches
Experience working with clinical data
Expertise in applying computational biology methods to the process of drug discovery, such as methods used for disease modelling and target discovery, combination strategies, as well as biomarker development.
Experience applying computational biology workflows on GCP
Strong experience in Python
Hands-on experience in applying ML (especially deep learning) models in the field of computational biology.

Culture and values
What does it take to be successful at IsoLabs? It's not about finding people who think and act in the same way, but we do have some shared values:

Thoughtful
Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day.

Brave
Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less.

Determined
Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we.

In this together
Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere.

Creating an inclusive company
We realise that to be successful we need our teams to reflect and represent the populations we are striving to serve. We’re working to build a supportive and inclusive environment where collaboration is encouraged and learning is shared. We value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact.

We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Hybrid working
It’s hugely important for us to be able to share knowledge and establish relationships with each other, and we find it easier to do this if we spend time together in person. This is why we’ve decided to follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tue, Wed, and one other day depending on which team you’re in). As an equal opportunities employer we are committed to building an equal and inclusive team. If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.

Please note that when you submit an application, your data will be processed in line with our privacy policy.

BS Computer Science, Bioinformatics, Information Systems, etc. MS preferred.
Data Structures / Algorithms Coursework

Knowledge, Skills And Abilities

Containerization: Docker (preferred), Singularity
Orchestration: DNAnexus (preferred), SevenBridges, Azure / AWS Batch, Cromwell, Kubernetes, Toil, miniWDL, AWS Omics (preferred)
Orchestration Language: WDL (preferred), CWL, YAML, Nextflow, Snakemake
Cloud: AWS, Azure, Google, AliBaba
Programming Language: Python (preferred), R, Java
Source control: GitLab (preferred), Bitbucket, GitHub, TFS
Extensive analytic troubleshooting skills
Excellent communication and organizational skills, especially for problem solving under pressure
Strong technical documentation skills
Eagerness to acquire new skills in genetics
Ability to thrive in a fast-paced environment and manage multiple tasks independently

Preferred Technologies

High performance computing on a local cluster
Bioinformatics Tools: GATK, SAMtools, bedtools, bwa, primer3, etc.
Security / Privacy: HIPAA, GDPR
Biology: Next-generation sequencing, Sanger sequencing, MLPA, PCR, Southern Blot
Data science: Machine learning, deep neural networks

Tasks and responsibilities

You will play a significant role in the data analysis as well as further development, validating, implementation and integration of the genomics platform at the Princess Máxima Center. You will work in close collaboration with bioinformaticians and laboratory specialists, and pharmacists in both the Kemmeren group, the molecular diagnostic laboratory and the Maxima pharmacy.

Specific tasks include:

Validating the Pharmcat tool for analysis of Whole genome sequencing data and embedding the farmacogenetic analysis within the genomics platform
Operational analyses of Whole genome sequencing data.
Further development and implementation of the genomics platform using Molgenis, WDL, Cromwell, REST and large-scale computational infrastructures.
Support data resources used for clinical data analysis.
Setting up and supporting bioinformatic analysis pipelines.
Profile

We expect a highly motivated candidate good communication skills. You are flexible, versatile and a good team player in a dynamic multidisciplinary environment. You are also able manage short deadline (diagnostic) tasks and work in a structured manner with an attention to details.

In addition, you have at least:

A bachelor or master in bioinformatics or similar experience in bioinformatics or data science.
Excellent technical and programming skills are required, preferably in Linux, R, python and java.
Knowledge about next-generation sequencing, genetics, statistics and large-scale computational infrastructures.
Our job offer

We offer a fulltime position (36 hours per week) in a very stimulating and cross-disciplinary clinical and research environment, combining cutting-edge clinical care with state-of-the-art bioinformatics. You will initially be appointed for a period of 1 year with a possible extension. Your gross monthly salary will depend on experience and background, starting in scale 55 with a maximum of €4.842,- gross a month based on a fulltime position (36 hours). You also receive 8,33% gross monthly salary holiday allowance and 8,33 % end-of-year bonus. The Princess Máxima Center operates according to the collective labour agreement ‘cao algemene ziekenhuizen’.

Work environment

You will be part of the translational bioinformatics team at the Princess Máxima Center. This team is responsible for performing and developing bioinformatic data analyses at the interface of clinical care and research. The translational bioinformatics team is at the fore-front of implementing next-generation sequencing technologies in clinical practice including exome sequencing (WES), whole genome sequencing (WGS) and RNA-seq based analyses for all patients. Implementation of novel analysis within existing workflows as well as long-read technologies and other sequencing-based assays are under active development. We have extensive experience with implementing novel technologies in a diagnostic setting and coordinating bioinformatics infrastructures such as High-Performance Computing, workflow management systems and data sharing and collaboration facilities.

The Princess Máxima Center

The Princess Máxima Center for Pediatric Oncology is an integrated hospital and research institute, which integrates healthcare, research and education on pediatric cancer, in a single location in Utrecht. Our institute aims to provide the highest level of care for all children with cancer, with optimal quality of life. The center brings together the best possible care and scientific research, creating a unique interdisciplinary institute for pediatric oncology in Europe.

Contact

You can apply for this position using the apply button. We invite you to apply as soon as possible, since we will close the vacancy when we have found a suitable candidate. For more information, please contact Dr. Jayne Hehir-Kwa.

Acquisition as a result of this vacancy is not appreciated.

https://werkenbijprinsesmaximacentrum.nl/en/vacancy/clinical-bioinformatician/

Day - 08 Hour (United States of America)

From primary care to complex specialty care, Stanford Medical offers the highest quality health care services in a comfortable and caring environment. Our experienced and dedicated doctors, nurses, and staff are committed to providing individualized attention and personalized care. We are proud to be an affiliated hospital of Stanford University, where cutting-edge research and advanced medicine bring together state-of-the-art treatments and expert care. Our health care team works closely with each patient to provide comprehensive care and comprehensive services tailored to their unique needs. We are dedicated to delivering the highest quality health care in a safe, supportive setting.

This is a Stanford Health Care job.

A Brief Overview

Senior Staff Scientist will be part of a growing clinical genomics team of bioinformaticians, lab scientists, data curation scientists, clinicians and medical fellows. The Clinical Genomics Program (CGP) is a collaboration between Stanford Hospitals and Stanford School of Medicine to deliver best-in-class genomics services to the Stanford community. CGP plans to use a multi-omics (whole-Genome and transcriptome) analysis approach to diagnosis. This position is responsible for developing novel tools (LIMs, workflow automation) and algorithms (DNASeq and RNASeq) for use in a clinical diagnostics setting. This position will be responsible for evaluating current algorithms and tools and developing a "best-practice" set of methods; guiding and mentoring other junior members of the bioinformatics team; interfacing with the Variant Interpretation team to identify gaps in variant detection, annotation, and workflow support; and developing novel methods and tools to fill those gaps.

Locations

Stanford Health Care

What You Will Do
Develop novel algorithms for genome assembly, variant detection (SNPs and InDels) and structural variant detection (CNVs, Inversions and Translocations) for a clinical-grade genome analysis.
Develop novel methods to integrate different NGS technologies such as Short-reads and Long-reads (DNASeq) to solve analytical challenges.
Implement cloud-based analytical pipelines to process thousands of clinical whole genome sequencing (WGS) data sets.
Apply best practices in DevOps, using tools like Docker, Kubernetes, Terraform, and Ansible to manage cloud projects and automate building, testing, and deployment of software components.
Lead development work to maintain and improve distributed workflow management infrastructure, LIMS, and other critical infrastructure.
Analyze clinical datasets (including exome and whole genome sequencing) to generate clinical diagnostic reports.
Design and communicate plans for complex software projects using best practices in software development and robust design of distributed systems.
Identify and correct any weaknesses in systems or team processes related to security, completeness and quality of data analysis, efficient resource usage, or robustness.
Provide detailed technical assistance to other team members and foster a culture of cooperation and personal development.
Work closely with data curators and genetic counselors to identify opportunities to increase the overall solve-rate of clinical cases through better algorithms and tools.
Perform other related duties as assigned.
Education Qualifications
Graduate Degree (Ph.D, M.S with considerable experience will be considered) in Computer Science/Engineering, Bioinformatics, Mathematics, Statistics and other related fields.
Experience Qualifications
Ph.D. plus 3 or M.S plus 6 years of experience developing algorithms for NGS platforms (preferably in a clinical setting).
Knowledge, Skills And Abilities
Experience in leading algorithms/software development projects and teams.
Strong experience developing bioinformatics algorithms and tools used in NGS analysis as evidenced by publications and GitHub repositories.
Proficiency in Bayesian and non-Bayesian statistical genetic methodologies.
Experience developing Machine Learning algorithms is a plus.
Experience in automating management of distributed systems in the Cloud, including provisioning, administering, testing, and monitoring.
Experience with REST API design.
Experience with designing architecture of distributed systems.
Demonstrated experience with Cloud architecture and cloud-based dev-ops tools.
Experience with best practices, tools, and philosophies for modern software development (git, issue trackers, testing frameworks, Agile, CICD).
Demonstrated team leadership skills paired with deep technical expertise.
These Principles Apply To ALL Employees

SHC Commitment to Providing an Exceptional Patient & Family Experience

Stanford Health Care sets a high standard for delivering value and an exceptional experience for our patients and families. Candidates for employment and existing employees must adopt and execute C-I-CARE standards for all of patients, families and towards each other. C-I-CARE is the foundation of Stanford’s patient-experience and represents a framework for patient-centered interactions. Simply put, we do what it takes to enable and empower patients and families to focus on health, healing and recovery.

You will do this by executing against our three experience pillars, from the patient and family’s perspective:
Know Me: Anticipate my needs and status to deliver effective care
Show Me the Way: Guide and prompt my actions to arrive at better outcomes and better health
Coordinate for Me: Own the complexity of my care through coordination
Equal Opportunity Employer Stanford Health Care (SHC) strongly values diversity and is committed to equal opportunity and non-discrimination in all of its policies and practices, including the area of employment. Accordingly, SHC does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity and/or expression, religion, age, national or ethnic origin, political beliefs, marital status, medical condition, genetic information, veteran status, or disability, or the perception of any of the above. People of all genders, members of all racial and ethnic groups, people with disabilities, and veterans are encouraged to apply. Qualified applicants with criminal convictions will be considered after an individualized assessment of the conviction and the job requirements.

Base Pay Scale: Generally starting at $60.86 - $80.65 per hour

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, specialty and training. This pay scale is not a promise of a particular wage.

AI对科学的影响

地方不大，人员不多，是典型的创业企业的样子。“我们是去年搬过来的。这块是公司办公的地方，隔壁就是一个100多平方米的实验室。”施威扬对记者说。施威扬是上海绾塍生物科技有限公司创始人兼首席科学家。

术业有专攻，绾塍生物专注的，是单细胞测序技术的研发及其应用。这个听起来非常高大上的技术，其实人们的生活很近。“以当前在全球蔓延的新冠肺炎疫情为例。疫情发生以来，国内外有大量的科研论文发表，为什么会在短时间内有这么多研究发现？因为运用了单细胞分析技术；北大的科学家用2-3周时间就从康复期新冠患者的血浆的B细胞中，筛选出了多个有出色的抑制病毒感染活性的的中和抗体，为什么这么快？因为运用针对单个B细胞的测序分析技术；Facebook创始人马克·扎克伯格近日也宣布，将资助75万美元用于支持五个基于单细胞技术的新冠病毒病（COVID-19）研究项目。”

施威扬坚定地认为，单细胞技术一定是下一代精准医疗的基石。“之前的精准医疗仅仅停留在基因组层面，能够提供的信息极为有限，人体核心的功能单元其实是一个个的细胞，认识疾病实际上就是要理解病变的细胞发生了什么样的改变。未来的精准医疗，必将是对每一例患者中病变的细胞进行精准诊断，然后针对这些个体特异的病变细胞进行个性化的治疗。”他说。

单细胞技术媲美于显微镜

了解单细胞技术，要从生命科学上两个宏大的计划说起。

1990年，一项旨在于测定组成人类染色体中所包含的30亿个碱基对组成的核苷酸序列，绘制人类基因组图谱的“人类基因组计划”正式启动。经过十余年的努力，2001年2月12日，参与人类基因组计划的六国科学家公布了人类23对染色体DNA大规模测序的精确图谱。这是人类首次从分子视角探索生命的奥秘。这项被称为生命科学“登月计划”的研究也成为推动精准医学发展的基础性力量。

然而，随着人们对疾病认识不断深入，基于多细胞测序获得的数据无法满足一些复杂疾病诊断所需的颗粒度水平。因此，2016年10月，全球顶级科学家在英国伦敦启动了人类细胞图谱计划（Human Cell ATLAS，HCA），这项计划将测定人类全身40万亿个细胞中每种细胞的独特身份信息，并根据细胞间的协作路径绘制三维人类基因图谱。单细胞测序技术是HCA计划实施的重要底层技术。

与基于大量细胞样品的传统测序方法只能提供平均化了的数据不同，单细胞测序可以获取关于样品中每一个细胞的所有组学数据，明确样本中包含的细胞类型，并记录别个细胞所发生的特定变化。

“人类的疾病，大部分不是基因发生了改变，而是细胞发生了改变。单细胞技术能够对每一个细胞进行精准测量，从而实现对疾病的个性化诊断和治疗。如果说基因测序是精准医疗的1.0时代，那么，单细胞测序是精准医疗的2.0时代.” 施威扬解释说，“通俗地说，基因测序看到的是‘一团’细胞，而单细胞测序能够看到一个个细胞。因此，单细胞技术对于生物医学的革命性意义可以和显微镜的发明相比较，因为二者都可使研究者真正看到单个细胞的细微差异。”

有点偶然的创业
从大学本科开始与生物学结缘，施威扬在这一领域耕耘至今。1993年，获得国际化学奥林匹克竞赛金牌的他保送进入清华大学生物系学习，本科毕业后赴美留学，2003年在美国华盛顿大学获得博士学位，后在加州大学伯克利分校从事博士后研究，主要用高通量测序技术研究早期胚胎发育的分子调控机制跟非编码RNA的生物学功能。

从2013年开始，施威扬转向单细胞测序技术的研究。最初的出发点，主要是用于自己科研。那么，是什么因素促使他生发了创业的念头，致力于将单细胞测序技术走向市场，走向商业？

施威扬表示，创业有内外两个方面的原因。从内因说，是他掌握了单细胞测序技术之后，找他合作的实验室越来越多，项目的规模也越来越大，这让他意识到单细胞测序技术未来市场需求的潜力。外因则与当年清华大学生物系的同学吴子牛有关。“2017年的时候，吴子牛当时在做软件系统方案。他有一个客户，是一家飞机发动机公司。有一个难题困扰着这家公司，那就是发动机的油箱里会生长很多未知的细菌，影响油品的质量。吴子牛知道我在做单细胞测序技术，便来找我帮忙，看看有没有方法能够鉴定到底是什么种类的细菌，而我就提出单细胞基因组学技术恰恰适合这个问题。事情解决之后，我们两个越谈越投缘，我们认定单细胞测序技术不应该只停留在实验室，而是应该为生物学领域解决一些重大的问题于是两人决定一起联手创业。”

上海绾塍生物科技有限公司由此应运而生。公司专注于自主研发单细胞测序平台，包括微流控设备、微液滴芯片、多组学试剂、分析软件等，为客户提供全面和系统的单细胞分析解决方案。

施威扬对自己的公司非常自信。他认为，深厚的科研背景是公司的特质所在，也是其公司的竞争力之所在。“因为我们是一个长期研究单细胞生物学的团队，从大学的研究课题组，到产业界，我们始终站在单细胞技术研发和应用的前沿。对于其他的一些企业，他们可能直接是从一个具体的产品开始来做，而我们对单细胞技术的理解和布局则是系统和全面的。从低通量到高通量，从转录组到表观组，我们的科学研究和技术开发相辅相成，使得我们可以持续开发新的单细胞产品和技术，所以这是我们的跟其它公司整体定位的一些差别。”

做一个有全球影响力的企业
虽然还是一个初创企业，但上海绾塍生物科技有限公司在融资、客户拓展，产品研发等方面推进顺利。公司成立的第一年，便获得了500万的天使轮的融资，并获得“2019年上海最具投资潜力50佳创业企业”的声誉。目前，第二轮的融资正在洽谈之中，目标金额是2000~3000万元。市场拓展方面，公司已经拥有了国内的50家客户，其中包括医院、高校和研究机构、生物公司等。产品研发方面，该公司的产品现在涵盖了高通量和低通量的各种单细胞组学产品，包括转录组，基因组，表观组等，以及相应的数据分析服务。“我们正在研发一个仪器平台，年底就可以交给客户试用。” 施威扬说，“未来公司的产品线是两方面的，，一是销售仪器技术平台产品，一是提供单细胞分析系统解决方案。”

施威扬坦言，公司直接对标的企业是全球单细胞测序领域的独角兽——10X Genomics。这家全球高通量单细胞测序行业的领头羊企业从2016年推出第一代单细胞测序产品到去年在美国纳斯达克上市只用了短短的3年时间，市值一度高达100亿元美元。施威扬认为，从技术上说，该公司不逊色于10X Genomics，是在一个层次上的，“有些产品，我们优于它们，而且我们还有它们没有的技术。”

说到未来的企业愿景，施威扬说，从企业的角度来说，希望绾塍生物能够成为一个有全球影响力的企业，为全球的研究者提供单细胞测序分析和研究平台，加速精准医学向单细胞分析的全面转变；从技术服务民众的角度来说，则是希望能够提供低廉价格的单细胞技术服务，让单细胞实验系统像PCR仪一样，每个实验室都可以在日常研究中使用。最后，绾塍希望通过和上下游企业合作，建立完整的单细胞技术和应用生态链，推进单细胞技术迅速走进临床，造福广大疑难杂症患者。

Educational Requirements
A PhD in bioinformatics, computational biology, related field of research, or MSc with 2+ years experience (preferably industry).

Responsibilities
Act as the key bioinformatics scientist for internal programs to provide in-depth support for new target exploration and validation, NGS related experiment design and analysis, clinical biomarker test platform evaluation and vendor selection, omics related clinical biomarker analysis
Designing, developing and deploying robust workflows to analyze high dimensional omics data, with emphasis on single cell and bulk transcriptome, exome, proteome and CRISPR screens
Mining proprietary and public biological and biomedical data to generate novel hypotheses or insights
Internalize and manage external multi-omics data by developing Rshiny apps
Lead review and evaluation of new technology, platform and vendors
Collaborate closely and effectively as a member of global biomarker and translational research team, follow sound scientific practices, and maintain effective documentation of activities and analysis.
Presenting analysis results in a clear and concise manner with well-designed presentation materials
任职条件:

Qualifications：
PhD degree in bioinformatics, computational biology or related fields. For Principal Investigator position, 3 years or more industry experience is required.
Strong programming and scripting abilities in R, and proficient in at least one other programming language (Python, Perl, Shell scripting, Java etc.)
Comfortably working with Linux system and server/cloud computing environment
Excellent background in analyzing high-throughput biomedical data (RNASeq, scRNAseq, ExomeSeq, GenomeSeq, spatial gene expression profiling and human genetics, etc.): data cleaning, functional annotation, normalization, analysis, interpretation and visualization
Strong statistics and math background, experience with machine learning is a plus.
Familiarity with public databases: TCGA, CCLE, HPA etc.
Experience in database design, analysis pipeline and Rshiny development
Strategic, Self-motivated and enjoys teamworking within an international team and dynamic environment always with timeline in mind
Thorough understanding or proof of strong interest in tumor biology, immunology, inflammation, and drug discovery
Excellent communication skills
Fast learner and excited for new challenges

We are seeking a talented Computational Biologist to join our Data Science team at the Roche Innovation Center Shanghai. In your role you will work with AI researchers and bioinformaticians to develop computational methodologies in understanding disease biology and discovering drug targets. You will also collaborate with scientists from various drug discovery functions to contribute directly to drug projects. This role requires strong biology knowledge and computational skills in combination with an excellent capacity to communicate and lead in a multi-disciplinary environment. You will be a self-motivated and focused scientist who brings new ideas, energy and agility to the team that is passionate about discovering innovative medicines for patients with unmet medical needs.

Partner with AI researchers and bioinformaticians to develop novel computational methods to infer causality in disease progression
Analyze multi-omics and phenotyping data from research studies, clinical trials and real world databases to identify disease-driving cell types, pathways, and genes
Propose drug targets based on the biology insights derived from data and suggest validation experiments
Work closely with biologists to solve biological questions and validate computational findings
Contribute to drug projects by providing support on target validation, compound profiling, biomarker discovery, patient stratification, clinical trial design, etc
Communicate with data scientists across Roche to learn from each other and to collaborate on projects
Have the opportunity to lead data science/AI initiatives and projects
Who you are

You’re someone who wants to drive your own development. You’re looking for a company where you have the opportunity to pursue your interests across functions and geographies. In hiring new employees, we look for people who are also inspired by our mission and who would fit in well with the collaborative, rigorous and entrepreneurial spirit of the company’s global culture.

You have a Ph.D. degree in biology, immunology, computational biology or a relevant field. Additionally you bring the following characteristics:
Passion for in-depth understanding of biological questions and finding plausible answers with data analytics
Excellent analytical capability, being able to identify key questions and come up with innovative solutions
Deep biology knowledge, preferrally in immunology or oncology
Strong expertise in analyzing single-cell RNAseq data, biological pathways or networks, real world data, etc
Experience of text analytics is a plus
Good programming skills in Python or R
Good communication skills in English and Mandarin
Collaborative team player
Job Level:

Individual contributor
https://www.linkedin.com/jobs/search/?currentJobId=2808564658&keywords=single cell

抗体发现平台是不是对软件也有需求？

We are looking for a talented Scientist- Bioinformatics R&D to join our team. The Bioinformatics Scientist leads translational bioinformatics and product development for NGS pipelines as part of the R&D Bioinformatics department. This scientist is an integral part of an interdisciplinary team that develops computational methods and pipelines to interpret large-scale human genome and transcriptome sequencing data from reproductive health, cancer, and other diseases. As part of a development team of engineers and scientists, this scientist will translate research prototypes into production-quality, scalable pipeline products used by a variety of clinical diagnostics and research projects across many teams at Sema4. This scientist will serve as an authority in these products to other users and teams and optimize them to serve Sema4 data science needs.

RESPONSIBILITIES

Design, develop, and test NGS pipelines for clinical tests and research projects in oncology, reproductive health, and other indications.
Lead or support bioinformatics projects to translate NGS results, as well as public and internal genomic, phenotype, and clinical/EMR datasets, to features and optimizations of clinical utility.
Analyze and integrate heterogeneous NGS data (somatic and germline SNVs, indel variants, copy-number alterations, structural variants, gene fusions, transcript isoforms, RNA abundance, RNA editing and modification) from diverse next-generation sequencing assays (Illumina, Ion Torrent, Pacific Biosciences; targeted panels, whole-exome sequencing, whole-genome sequencing, RNA-Seq; bulk and single-cell) and microarrays.
Work with wet labs and clinical teams to plan and design experiments to generate such data, and analyze this data.
Communicate effectively with collaborators (computational and bioinformatics scientists on R&D and production teams, IT/HPC, clinical lab directors, knowledgebase and curation teams, wet lab staff) to understand and satisfy product and research analysis needs.
QUALIFICATIONS

PhD in Bioinformatics, Biomedical Informatics, Computational Biology, Genomics, or a related discipline requiring strong computational and analytical skills supplemented with biology background
Hands-on experience working with NGS tools with high proficiency, especially for sequence analysis and expression analysis
Strong coding proficiency in R, Python, and SQL programming languages in a Linux environment.
Well-versed in the art of effective communication on interdisciplinary teams (scientists, programmers, and clinicians), especially graphical communication about high-complexity datasets to scientific audiences from different backgrounds.
High self-motivation, great ability to work in both multiple-task and independent fashions.
Good understanding of molecular, cell, and developmental biology, especially where relevant to cancer genomics, oncology, or endocrine neoplasms, and especially molecular cloning and NGS library preparation methodologies.
Developing code using distributed version control tools (especially Git) and software issue tracking/management systems (especially Jira).
Using or developing genome browsers or other tools for visualization of genomic datasets.

At Genospace, our mission is to be the leading information platform for applied precision medicine. Our interdisciplinary team is merging the tools and techniques of genomics, healthcare, data analytics, web development, and cloud computing. We serve research, clinical development, pathology, and clinical care customers who work with high-dimensional genomic and other biomedical data. Many of the most advanced precision medicine organizations are powered by Genospace.

Your Impact:

Your work as a Senior Software Engineer at Genospace will impact individuals and organizations across the healthcare landscape: patients searching for the best treatment options, researchers seeking to make advances based on a sea of high-dimensional data, physicians deploying personalized medicine in everyday practice, and laboratories conducting some of the most advanced analyses in the world.

What You’ll Do:

Collaborate with product, design, and data science teams to design, develop, and deliver new product features and enhancements
Provide technical leadership and support throughout the engineering process, from architecture and design to monitoring performance and resolving production issues
Mentor and coach junior and mid-level engineers
Participate in regular peer design and code reviews
Set an example for quality in work, demonstrating, teaching and enforcing engineering best practices in design, development and testing
Foster an engineering culture of continuous improvement, quality, collaboration, humility, and respect
What We’re Looking For:

Capacity to deliver on large, complex tasks with multiple components; investigate and resolve areas of significant ambiguity; identify the work and break down tasks contributing to the team’s objectives over a 2-3 month timespan
Ability to contribute across our stack:
Front End – Vue.js
Back End – Java, Groovy, Grails, Kafka, Micronaut
Data Tier – MongoDB, Elasticsearch
Automated testing – Geb, Selenium
Ability to foresee and test against potential functional and scalability problems and own issues through resolution
Ability to determine accurate and dependable delivery estimates
Ability to identify areas of inefficiency and own the implementation of improvements
A self-starter that uses good judgment in how best to apply their time effectively
Strong commitment to teamwork and a humble attitude
Leadership potential including oversight of junior personnel and the ability to identify areas of improvement and work with individuals to maximize their effectiveness
An interest in making an impact on healthcare and clinical research through technology
Clear and effective communication with technical and non-technical audiences
Education & Background:

Bachelor’s degree in Computer Science, Software Engineering, or equivalent experience
5+ years of professional experience in software development

COVID-19 Considerations:

Genospace is adhering to CDC, State and local orders with regard to COVID-19. The health and safety of our colleagues and their families, as well as potential candidates, is our highest priority.

Due to COVID-19, Genospace has transitioned to a work-from-home model, with working hours based on Eastern Time. Employees are welcome to use our flexible, co-working space, but are not required to come into an office. Please note, this is a remote position.

Genospace is an equal opportunity employer and does not discriminate based on any of the following: race, religious creed, color, age, sex, sexual orientation, gender identity, gender expression or gender characteristics, national origin, religion, marital status, medical condition, physical or mental disability, military service or veteran status, pregnancy, childbirth and related medical conditions, or any other classification protected by federal, state, and local laws and ordinances.

https://www.technologynetworks.com/genomics/articles/genome-sequencing-in-modern-medicine-an-interview-with-genomics-england-347160
提到的几个重要的应用方向:
cancer
Mendelian diseases(rare diseases)
infectious diseases
Pharmacogenomics
disease prevention

Position Description

The New York Genome Center is looking for a highly motivated, detail-oriented individual to join our rapidly expanding Clinical Informatics division within the NYGC CLIA Laboratory. As a Bioinformatics Analyst specializing in molecular diagnostics, you will be responsible for the analysis of next-generation sequencing (NGS) data for cancer conformant to CLIA / CLEP guidelines. You will work as part of a team of highly experienced laboratory and informatics staff and scientists at the NYGC CLIA Laboratory. You will be asked to perform variant calling analysis from whole genome/whole exome patient sample sequencing data. You will be part of a team of CLIA scientists and laboratory personnel taking an active part in generating, developing and reporting patient sample genomic profile reports. You will be responsible to help implement and benchmark the most up to date variant calling algorithms used in clinical sequencing. You will assist clinical informatics and laboratory scientists in developing and validating new NGS based clinical laboratory tests. You will help identify and QC NGS somatic variants for molecular diagnostic reporting purposes. You will use your experience in NGS variant calling analysis while participating in retrospective research of clinical oncology data.* We anticipate that this position will be remote through June 2021.*

Required Experience

Key Responsibilities
Analyze clinical oncology sequencing data using established workflows
Implement and execute analysis pipelines and workflows
Assist in producing final CLIA oncology molecular diagnostics reports
Develop and apply novel analysis approaches to aid clinical sample variant prioritization
Benchmark new tools for sequencing data analysis and propose improvements
Analyze validation experiments for laboratory developed tests (LDT)
Summarize results in written or oral reports for CLIA laboratory personnel at weekly internal meetings or collaborating scientists and oncologists at external tumor boards
Assist CLIA laboratory personnel in preparing data, text and figures for case analysis, LDT validation proposals, manuscripts and external presentations
Perform and evaluate appropriate sequencing QC measures
*

Required

Requirements & Qualifications
MS degree with 3+ years work experience in cancer or hereditary disease next generation sequencing (NGS) analysis or PhD in cancer genomics or human genetics with demonstrable biomedical NGS bioinformatics skills required
Background in oncology or disease-focused genomics
Strong programming skills in Python and shell scripting
Work experience with various sequence analysis tools, including BWA, GATK, Picard, samtools, etc.
Work experience and algorithm understanding of standard variant calling tools, such as but not limited to MuTect, Strelka, VarScan, Pindel, Bic-Seq, Facets, Crest, Delly, Fusioncatcher, Haplotypecaller or equivalent
Knowledge in the analysis of SNV, Indel, CNV and structural variants
Familiarity with various NGS QC principles
Work experience with commonly used public genomics datasets (1000 genomes, ExAC, OMIM, ClinVar, HGMD, CIViCDB, PharmGKB, OncoKB etc.)
Details-oriented, well-organized and an interest in clinical sequencing and disease related or cancer genomics
Team oriented with excellent written and verbal communication skills

Preferred
Prior experience working in CLIA environment is a plus
Experience in variant calling benchmarking and clinical validation analysis (eg. concordance, limit of detection, assay reproducibility)
Programming skills in R
Experience of working in a Linux environment, experience with SGE

Competencies
Technical and Professional Skills: Consistently demonstrates skills and knowledge relevant for current role; strives to expand the depth and breadth of technical and professional skills; works with a high level of integrity; exhibits focus and discipline; appropriately prioritizes, manages expectations and delivers on commitments.
Collaborative & Communicative: Models collaboration and teamwork; brings out the best in others; effectively works with all levels, internally and externally; respects and embraces diversity of perspective; communicates clearly and listens carefully; uses good judgment as to what to communicate and when to do so.
Adaptable & Innovative: Adaptable and embraces change; develops new insights and pursues improvements and efficiency; fosters exchange of new ideas and willing to challenge the status quo; takes initiative and is solution-oriented; engages in work with passion and curiosity.

About The New York Genome Center

The New York Genome Center (NYGC) is an independent, nonprofit, academic research organization dedicated to advancing genomic research. NYGC scientists and staff are furthering new approaches to diagnosing and treating neurological diseases and cancer through their unique capabilities in whole genome sequencing, RNA sequencing, state-of-the art analytics, and the development of genomic tools. NYGC concentrates specifically on disease-based research in the following areas: neuropsychiatric disease (autism, schizophrenia, bipolar); neurodegenerative disease (ALS, Alzheimer's, Parkinson's, Huntington's), and cancer.

Located in Lower Manhattan, the New York Genome Center was founded by and remains closely affiliated with twelve leading academic medical centers and research universities in the New York region and beyond, engaging in research projects with and for these institutions. Essential to our collaborative work is an outstanding faculty, whose members typically hold a joint appointment at NYGC and a partner university. They support our scientific mission by conducting independent research in areas of mutual interest to us and the wider scientific community.

Equal Opportunity

Diversity, equity, and inclusion are central to the core mission at the NYGC. We strive to create a workplace environment that is welcoming and fair to all regardless of race, ethnicity, gender, sexual orientation, physical ability, or religion. We believe that when people of various backgrounds, life experiences, and perspectives work together in an inclusive and equitable environment we gain new and valuable perspectives that otherwise would have been missed. Valuing and supporting all NYGC employees as individuals while helping them realize their full potential is critical to promoting greater collaboration, innovation, and discovery - fostering a sense of belonging for our greatest strength, our people. We recognize that there is still work to be done that will require sustained commitment from the entire organization.

The New York Genome Center is a VEVRAA Federal Contractor. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, creed, color, gender, religion, national origin, sexual orientation, age, disability, genetic predisposition or carrier status, protected veteran or military status, domestic violence victim status, partnership status, caregiver status, alienage or citizenship status, marital status, or any other characteristic protected by applicable law. The New York Genome Center takes affirmative action in support of its policy to hire and advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities.

FLSA Status - Exempt

This position is eligible for visa sponsorship and relocation assistance.

Tracking Code: 443-105

Job Location: New York, New York, United States

Position Type: Full-Time/Regular
Seniority Level
Associate

Industry
Research Biotechnology Hospital & Health Care
Employment Type
Full-time

Job Functions
Research Analyst

Clinical Genomics and COVID-19. Updates and breakthroughs in genomics medicine • Discussions around pandemic response clinical research • Clinical practise • Special educational sessions for the NHS and Genomic Counsellors • Digital pathology • Infectious diseases • Clinical applications of synthetic biology • Polygenic risk scores • Case genomics in critical care

Genomics in Research. Exploring the dark genome • Structural variation detection • Long range sequencing • Nanopore sequencing • The human microbiome • Epigenetics • Histogenomics • Sequencing technology and patent battles • Single cell analysis • Spatial genomics • RNA sequencing

Biodata. Machine learning/AI • Biodata in drug discovery and development • Population diversity • Understanding phenotype • Genome-wide association studies (GWAS) • Multi-omics and phenotypic data integration • Data-driven innovation • Knowledge graphs • Real World Data

Rare Diseases. Translating research into practice • The European Joint Programme on Rare Diseases • Rare disease community experiences • Early detection and diagnosis
Healthcare Data. Leveraging data for better patient outcomes • Equitable access • Diversity in genomics datasets • Creating self-learning healthcare systems • Ethical practices • Geospatial analytics

Drug Discovery and Development. Companion diagnostics • Pharmacogenomics • Functional genomics • Target identification and validation • AI/Natural Language Processing (NLP) • Toxicity prediction

Cancer Genomics. Liquid biopsies • Precision oncology • NGS testing and technologies • Cancer research • Artificial intelligence

Down the Rabbit Hole. The Darwin Tree of Life Project • Food production • Industrial chemistry • Pathogen engineering • NASA/space research and exploration

Abdul launched NVIDIA’s Health platform, Clara, to reach thousands of developers and deployment sites.