Scientist, Computational Biology

What You Will Contribute To Altos

The ideal candidate will contribute to innovative aging and rejuvenation research efforts using large-scale omics data, collaborate across disciplines, and help develop tools that drive our scientific goals forward.

Responsibilities:

• Design and execute computational strategies to analyze multi-omics data, including bulk and single-cell transcriptomics, chromatin accessibilityATACseq, ChipSeq, Cut&Run/Cut&Tag, DNA methylation, and spatial transcriptomics, in support of studies in aging and rejuvenation.
  Apply and develop bioinformatics tools, statistical models, and machine learning approaches to uncover biological insights.
  Evaluate and synthesize recent scientific literature to inform the design of computational pipelines and improve research strategies.
  Maintain clear, complete, and organized records of all analyses and workflows in reproducible formats (e.g., notebooks, scripts, documentation).
• Present findings in internal lab meetings and cross-functional seminars.
• Contribute to the writing of progress reports.
• Provide guidance and mentorship to students, technicians, and junior scientists, when applicable.

Who You Are

You are an intellectually curious scientist with strong analytical skills, a passion for computational biology, and a collaborative spirit. You’re excited to explore the biology of aging and help develop approaches to understand and potentially reverse its effects.

Minimum Qualifications

• PhD in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related field.
• Proven experience in the analysis of genomic and transcriptomic datasets, particularly from high-throughput sequencing technologies.
• Proficiency in programming (e.g., Python, R) and experience working with standard bioinformatics tools and data repositories.
• Strong foundation in statistical analysis, machine learning, or probabilistic modeling.
• Demonstrated ability to work independently and collaboratively in an interdisciplinary research environment.
• Track record of scientific publications in peer-reviewed journals.

Preferred Qualifications

• Experience in single-cell or spatial omics
• Familiarity with methods for multi-omics data integration.
• Working knowledge of deep learning, variational inference, or generative modeling techniques is a plus.
• Experience contributing to open-source software or the development of reproducible pipelines.

The salary range for San Diego, CA:

• Scientist I, Computational Biology: $137,400 - $176,200

Exact compensation may vary based on skills, experience, and location.

 

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