Computational Biologist

Key Skills

3D Modeling & Rigging, Algorithm intelligence, Bioinformatics, Business Development, Common data structures, Computational Algorithms, Data modernization, Data science techniques, Design, Genetics, Logic-analyze, Mathematics, MS Dynamics, Oil Technology , Pandas, Product Development, Python Programming, Sampling methods, Statistical modeling, Terabyte scale datasets

Job Description

At Invitae, our mission is to empower doctors and patients to use genetic and genomic information to make informed medical decisions at all life stages. The Clinical Science and Interpretation (CSI) team plays a critical role in expanding our genomics platform and medical interpretation capabilities by designing and developing robust, quantitative and clinically informed modeling systems.

We have an available opening in our CSI team for talented and motivated Computational Biologists with expertise developing computational methods to analyze and model complex biological datasets and processes. As a core member of this team, the primary responsibility of Computational Biologists is to contribute to the development and scalable deployment of diverse, integrated computational and cellular systems that can provide key support for clinical interpretation of genetic testing results. The team is highly cross-functional and multi-disciplinary. You will work alongside genomic scientists, biophysicists, cellular engineers, data scientists, AI engineers, software engineers, genetic counselors, and medical geneticists to bring improved healthcare to patients.

Our team is committed to advancing the science and technology of genetic testing. This commitment requires us to integrate and foster the knowledge and growth of diverse domain expertise in biological, computational, and clinical sciences. Your ability to apply advanced quantitative analyses in the understanding, quality control, and modeling of data from functional genomics assays, computational simulations, clinical genomics, and other diverse types of biological data will help define state-of-the-art genetic testing.

What you’ll do:

• Design, develop, and validate advanced computational methods and model complex biological processes and datasets, including data from large-scale mutational analyses, functional genomics assays (e.g. single-cell RNA-sequencing), molecular (e.g. protein) structures, dynamics and complexes, statistical genetics approaches and more.
• Develop, implement, and validate the application and use of modern data science techniques –that build on principles of statistics and methods for the design of experiments– to allow rigorous model evaluation, uncertainty quantification, prediction, and data generation.
• Integrate advances in diverse fields of biological, computer, and clinical sciences into modern computational infrastructure and workflows.
• Work in a highly collaborative and cross-disciplinary team to deliver quantitative, mechanistic, and scalable support for clinical interpretation of genetic results.

What you bring:

• Advanced degree (e.g. Ph.D.) in a quantitative discipline such as Computational Biology, Computer Science, Genome Sciences, Biophysics/Physics, Systems Biology, Bioinformatics, ML/AI or Mathematics.
• Experience developing and implementing rigorous computational methods and solutions to analyze complex biological datasets and processes. Direct experience working with large datasets is ideal, such as functional genomics (e.g. scRNA-seq data), biophysics (e.g. molecular dynamics), OR population genomics.
• High proficiency in scientific computing, with strong knowledge of modern data science techniques and numerical methods, and direct experience in algorithm development and machine learning. Experience with bayesian modeling and probabilistic programming is a plus.
• Ability to work independently, design and conduct research, and to evaluate, interpret and present complex scientific data.
• Ability to work effectively in a highly cross-functional environment where collaboration across disciplines is a key component for team success
• Excellent verbal and written communication and presentation skills
• Fluency in programming in Python, including familiarity with pandas, numpy