Scientist / Senior Scientist, Computational Biology

Scientist / Senior 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 and integrate multi-omics data, including bulk and single-cell transcriptomics, epigenomics (ATACseq, ChipSeq, Cut&Run/Cut&Tag, DNA methylation), spatial transcriptomics, proteomics and related high-dimensional data sets, in support of studies in aging and rejuvenation.
• Develop and implement robust and scalable bioinformatic pipelines, statistical models, and machine learning approaches to uncover biological insights.
• Collaborate closely with wet-lab scientists and cross-functional computational teams to translate biological questions into analytical strategies and actionable insights.
• Evaluate and synthesize recent scientific literature to inform the design of computational pipelines and improve research strategies.
• Evaluate and integrate emerging computational, AI, and deep learning methodologies to enhance analytical capabilities and discovery efforts.
• Build interactive visualization and data exploration tools to support interpretation, communication, and decision-making across teams.
• 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 a collaborative and innovative research environment, including mentoring junior scientists or trainees where appropriate.

Who You Are

You are an intellectually curious scientist excited and inspired by the Altos mission of restoring cell health and resilience to reverse diseases, injury and age- related disabilities. You are keen to explore the biology of aging to develop approaches to understand and potentially reverse its effects.

You possess strong analytical skills, a passion for computational biology, and a collaborative spirit with the ability to work within and contribute to Project Teams and within a matrix structure. The ideal candidate is:

• Self-motivated to drive and deliver on projects and goals
• Excited to work in a fast-paced, multidisciplinary environment.
• Focused on professional growth and expanding their skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in their field and apply knowledge to their work.

Minimum Qualifications

• PhD in Life Science or Computational Biology: Level will depend on experience:

Scientist II (3- 5 years experience post PhD)

Senior Scientist I (6 years experience post PhD) 

• Proven experience analyzing and integrating high-throughput omics datasets using computational and statistical approaches.
• 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.
• Ability to translate complex scientific questions into computational strategies and analytical frameworks.
• Demonstrated ability to work independently and collaboratively in an interdisciplinary research environment.
• Strong communication and problem-solving skills, with the ability to present computational analyses to both expert and non-expert audiences.
• Track record of scientific publications in peer-reviewed journals.

Preferred Qualifications

• Background in cellular aging, rejuvenation, cellular plasticity, and/or reprogramming biology.
• Experience in single-cell or spatial omics, epigenomics, long-read sequencing, proteomics, and/or Ribo-seq technologies.
• Familiarity with methods for multi-omics data integration.
• Familiarity with machine learning, deep learning, or generative modeling approaches applied to biological data.
• Experience developing reproducible workflows using tools such as Nextflow and cloud computing environments (e.g., AWS).
• Previous wet-lab experience is considered a plus.

 Hiring Ranges:

Scientist II (3- 5 years experience post PhD) £62, 400- £82,100

Senior Scientist I (6 years experience post PhD) £79,200- £104,200