Scientist / Senior Scientist, Computational Biology in Cambridge

Scientist / Senior Scientist, Computational Biology in Cambridge

Cambridge Full-Time 62400 - 82100 € / year (est.) No home office possible
Altos Labs

At a Glance

  • Tasks: Join us in pioneering research to rejuvenate cells and reverse diseases using cutting-edge computational biology.
  • Company: Be part of Altos Labs, a top biotech company focused on innovation and inclusivity.
  • Benefits: Enjoy competitive salaries, professional growth opportunities, and a collaborative work environment.
  • Other info: We value diversity and foster a culture of belonging for all employees.
  • Why this job: Make a real impact in the field of aging and cell health while working with brilliant minds.
  • Qualifications: PhD in Life Science or Computational Biology with experience in high-throughput omics data analysis.

The predicted salary is between 62400 - 82100 € per year.

Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.

Altos Labs has been named one of the Top 3 Biotech Companies and ranked for the second year on the Forbes 2026 Best Startups in America list. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.

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.

We value collaboration and scientific excellence. We believe that a culture of belonging is foundational to scientific innovation and inquiry. Altos Labs provides equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Altos prohibits unlawful discrimination and harassment.

Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.

Scientist / Senior Scientist, Computational Biology in Cambridge employer: Altos Labs

At Altos Labs, we are dedicated to fostering a culture of innovation and collaboration, where exceptional scientists unite to advance our mission of restoring cell health and resilience. Our commitment to diversity and inclusion ensures that every employee feels valued and empowered, while our focus on professional growth provides ample opportunities for career development in a fast-paced, multidisciplinary environment. Located in a vibrant area, we offer competitive salaries and a supportive atmosphere that encourages exploration and creativity in the field of computational biology.

Altos Labs

Contact Detail:

Altos Labs Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Scientist / Senior Scientist, Computational Biology in Cambridge

Tip Number 1

Network like a pro! Reach out to people in your field on LinkedIn or at conferences. A friendly chat can lead to opportunities that aren’t even advertised yet.

Tip Number 2

Show off your skills! Create a portfolio or GitHub repository showcasing your projects and analyses. This gives potential employers a taste of what you can do beyond your CV.

Tip Number 3

Prepare for interviews by practising common questions and scenarios related to computational biology. Be ready to discuss your past projects and how they relate to the role at Altos.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our mission.

We think you need these skills to ace Scientist / Senior Scientist, Computational Biology in Cambridge

Computational Biology
Omics Data Analysis
Bioinformatics Pipelines
Statistical Modelling
Machine Learning
Data Integration
Programming (Python, R)

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the Scientist/Senior Scientist role. Highlight your experience with omics data and computational strategies, as this will show us you understand what we're looking for.

Show Your Passion:Let your enthusiasm for computational biology and our mission shine through in your application. We want to see that you're not just qualified, but genuinely excited about restoring cell health and resilience.

Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your skills and experiences, especially how they relate to the responsibilities listed in the job description. We appreciate clarity!

Apply Through Our Website:Don't forget to submit your application through our official website. This ensures we receive all your details correctly and helps us keep track of your application. Plus, it’s the best way to get noticed by our team!

How to prepare for a job interview at Altos Labs

Know Your Science

Make sure you brush up on the latest research in computational biology, especially around aging and rejuvenation. Familiarise yourself with key concepts and methodologies mentioned in the job description, like multi-omics data analysis and machine learning approaches. This will help you demonstrate your expertise and passion during the interview.

Showcase Your Collaboration Skills

Since the role involves working closely with wet-lab scientists and cross-functional teams, be prepared to discuss your previous collaborative experiences. Share specific examples of how you've successfully worked in interdisciplinary environments and how you can contribute to a culture of belonging at Altos Labs.

Prepare for Technical Questions

Expect to face technical questions related to programming languages like Python or R, as well as bioinformatics tools. Brush up on your statistical analysis skills and be ready to explain how you've applied these in past projects. Practising coding problems or discussing your previous work can give you an edge.

Communicate Clearly

You’ll need to explain complex scientific concepts to both expert and non-expert audiences. Practice articulating your research findings and methodologies in simple terms. This will not only showcase your communication skills but also your ability to make science accessible, which is crucial for fostering collaboration.