Machine Learning Computational Biologist

Key Skills

Algorithms, Bioinformatics, Data structuring, Machine learning techniques, Python Programming, RNA-seq Data processing, Statistics

Job Description

Calico is seeking a Machine Learning Scientist to join a team investigating aging and disease using genetics and functional genomics in humans and model systems. Genomics offers rich, informative profiles of organism state throughout life. We collect these data to build causal models for organism state, that reveal the critical underlying cellular processes and highlight promising intervention points. The ideal candidate is passionate about unraveling how genome sequence determines function and the adverse transformations that accompany aging.

Predictive modeling with cutting edge machine learning tools are at the core of this work, exemplified by recent publications modeling regulatory activity as a function of DNA sequence using deep learning.

• Avsec, Ž. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat Methods 18, 1196–1203 (2021).
• Yuan, H. & Kelley, D. R. scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks. Nat Methods 19, 1088–1096 (2022).
• Linder, J., Srivastava, D., Yuan, H., Agarwal, V. & Kelley, D. R. Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation. bioRxiv (2023).

Additional research can be found here,

This work benefits from world-class computing infrastructure and continued collaboration with top machine learning researchers within Alphabet.

Position Responsibilities:

• Develop novel computational methods for biological sequence analysis, single cell genomics, and statistical genetics
• Interact closely with experimental biologists to analyze large-scale genomics data to reach biological insights that inform Calico’s pursuit
• Communicate research via publications, presentations, web interfaces, and open software

Position Requirements:

• PhD in computational biology, bioinformatics, computer science, or a related discipline
• Strong computational fundamentals including machine learning, algorithms, data structures, and statistics
• Strong molecular biology and genetics knowledge and interest; familiarity with biological data resources
• Fluent coding in preferably Python but at least one common bioinformatics programming language
• Experience analyzing genomics experiments (e.g., RNA-seq, ATAC-seq, ChIP-seq, scRNA-seq, scATAC-seq)
• Experience applying machine learning to biological problems
• Intellectual curiosity, attention to detail, consistent follow-through, proactive approach to collaborations, demonstrated ability to work in a team environment
• Must be willing to work onsite at least three days per week

The estimated base salary range for this role is $152,000 - $158,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.