Senior Computational Biologist, Omics

The Opportunity

State-of-the-art technologies that measure multiple cellular aspects of in-vitro biology are at the heart of insitro's efforts to accelerate drug development. Computational biology is key to elucidating the relationship between these phenotypes and human disease and translating them into actionable outcomes.

We are looking for an expert in omics data analysis, including deep understanding of cell biology and single cell transcriptomics, and fluent with state-of-the-art analysis techniques. Your expertise will help the team navigate the complexities developing disease relevant cell models and analyzing high throughput phenotypic screens, and ensure that the tools being developed are calibrated and effective, and that analyses are performed to the highest rigor and in line with best practices in the broader scientific community.

In this role, you will collaborate closely with experimental biologists and machine learning scientists, support the identification of novel phenotypes, the development of new screening paradigms, and advance our understanding of disease. You will utilize diverse machine learning and bioinformatic methods to perform diverse downstream analyses, including integrating with other data modalities, including imaging and human cohort data in order to extract insights about disease mechanisms. You will be part of a cross-functional team of life scientists, data scientists, bioengineers, software engineers, and machine learning scientists that strive to identify therapeutic targets and develop drugs of high efficacy and low toxicity. This role will be reporting to the Head of Computational Biology and ML-Omics . This is a hybrid position that requires you to be in our South San Francisco headquarters at least three days per week.

You will be joining a vibrant biotech startup that has many opportunities for significant impact. You will work closely with a highly talented team, learn a broad range of skills, and help shape insitro's culture, strategic direction, and outcomes. Join us, and help make a difference to patients!

• Analyze and interpret omics datasets from disease-relevant in-vitro models to identify potential therapeutic targets from perturbation screens
• Partner with experimental biologists to design, troubleshoot, and optimize high-throughput experiments and workflows
• Integrate insights from multimodal data (bulk/single-cell RNA-seq, microscopy, spatial proteomics, human cohort data) to understand disease mechanisms and generate therapeutic hypotheses
• Calibrate analysis tools and workflows, define performance metrics, and conduct benchmarking to select fit-for-purpose solutions
• Communicate findings clearly to cross-functional stakeholders through reports, visualizations, presentations, and publications

• Ph.D. in computational biology, systems biology, bioengineering, machine learning, or a related discipline, with 3+ years of working experience post graduation
• Extensive hands on experience analyzing single-cell and bulk RNA-seq data
• Experience working with functional genomic assays data (RNA/ATAC/ChIP-seq, etc)
• Experience analyzing data from perturbational screens (e.g. perturb-seq)
• An understanding of systems biology, molecular biology, or disease biology (e.g. neurological disorders, metabolic disorders)
• Experience with spatial proteomics and/or transcriptomics
• Strong programming skills and proficiency with Python scientific packages (i.e., numpy, pandas, scanpy)
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Committed to writing well-commented code and documentation, and familiarity with coding best practices (i.e. version control, code review)
• Publication record of meaningful contributions to high-quality work in relevant computational biology, systems biology, life sciences, or biomedical venues

Our target starting salary for successful US-based applicants for this role is $175,000 - $200,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.

In addition, insitro also provides our employees:

• 401(k) plan with employer matching for contributions
• Excellent medical, dental, and vision coverage as well as mental health and well-being support
• Open, flexible vacation policy
• Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)
• Quarterly budget for books and online courses for self-development
• Support to attend professional conferences that are meaningful to your career growth and role's responsibilities
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and cafe with daily lunch and breakfast for employees who are either onsite or hybrid
• Access to free onsite fitness center for employees who are either onsite or hybrid
• Access to a free commuter bus and ferry network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area

insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.

Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com, and if in doubt, contact us at info@insitro.com.

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