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Machine Learning Computational Biology Jobs (NOW HIRING)

NewLimit

Computational Biologist

South San Francisco, CA · On-site

$150K - $200K/yr

... and machine learning models to unravel the biology of epigenetic aging and disease using ... Description NewLimit is seeking a Computational Biologist to join our Predict team. In this role ...

Natera

OR · On-site

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics ...

Urus Group LP

Computational Biologist

Madison, WI

Ph.D. in Computational Biology, Systems Biology, Genome Science, or a related field. * Biology ... Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

Urus

Computational Biologist

Madison, WI

Ph.D. in Computational Biology, Systems Biology, Genome Science, or a related field. * Biology ... Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

AgSource

Computational Biologist

Madison, WI · On-site

Ph.D. in Computational Biology, Systems Biology, Genome Science, or a related field. * Biology ... Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

AgSource

Computational Biologist

Madison, WI

Ph.D. in Computational Biology, Systems Biology, Genome Science, or a related field. * Biology ... Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

Farm Systems

Computational Biologist

Madison, WI

Ph.D. in Computational Biology, Systems Biology, Genome Science, or a related field. * Biology ... Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

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Machine Learning Computational Biology information

What types of projects might I work on as a Machine Learning Computational Biology specialist?

As a Machine Learning Computational Biology specialist, you may work on projects ranging from analyzing large-scale genomic data to developing predictive models for disease risk or drug response. Typical tasks include designing and implementing machine learning algorithms to identify patterns in biological datasets, collaborating with biologists and clinicians to interpret results, and contributing to publications or presentations. You'll often be part of a multidisciplinary team, interacting with data scientists, laboratory researchers, and software engineers. This role offers the opportunity to work on cutting-edge biomedical research and have a direct impact on advancements in healthcare and life sciences.

What is a Machine Learning Computational Biology job?

A Machine Learning Computational Biology job involves applying machine learning techniques to analyze biological data, such as genomics, proteomics, and medical imaging. Professionals in this field develop algorithms and models to identify patterns, make predictions, and generate insights that can drive scientific discovery or improve healthcare. They typically work with large datasets, employing statistical and computational methods to solve complex biological problems. The role often requires expertise in programming, data science, and domain-specific biological knowledge. It is commonly found in academia, pharmaceutical companies, biotech firms, and healthcare institutions.

What are the key skills and qualifications needed to thrive in the Machine Learning Computational Biology position, and why are they important?

To thrive as a Machine Learning Computational Biology professional, you need a strong background in biology, statistics, computer science, and machine learning, typically supported by an advanced degree in a relevant field. Familiarity with programming languages such as Python or R, experience with bioinformatics tools, and knowledge of machine learning frameworks like TensorFlow or scikit-learn are commonly required. Strong analytical thinking, effective communication, and the ability to work collaboratively in interdisciplinary teams are highly valued soft skills. These qualifications are essential for solving complex biological problems, developing robust computational models, and effectively communicating findings to both technical and non-technical stakeholders.

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Infographic showing various Machine Learning Computational Biology job openings in the United States as of June 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution.
Fellow in AI/ML for Cellular and Protein Computational Biology

Fellow in AI/ML for Cellular and Protein Computational Biology

Harvard University

Cambridge, MA • On-site

Full-time

Posted 17 days ago

Harvard University rating

8.1

Company rating: 8.1 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

131st of 535 rated colleges and universities

Job description

Position
Details
Title
Fellow in AI/ML for Cellular and Protein Computational Biology
School
Faculty of Arts and Sciences
Department/Area
Kempner Institute for the Study of Natural and Artificial Intelligence
Position Description
The Kempner Institute at Harvard University seeks early-career researchers to help shape the future of AI as Kempner AI Fellows. We are looking for candidates with strong foundations in modern AI/ML and the ambition to develop new AI approaches for high-impact problems in cellular and protein computational biology.
This role focuses on applying modern AI/ML methods to protein and cellular biology, including protein structure prediction, protein-protein and small-molecule-protein docking, cell state prediction from large-scale Perturb-seq datasets, and multimodal modeling of protein function and cellular state.
We seek candidates with strong technical preparation in modern AI/ML, a demonstrated record of research accomplishment, and experience in computational biology or biological data analysis. Strong candidates may come from protein-focused, cell-state-focused, or multimodal biological modeling backgrounds and will have expertise in one or more of the following areas:
  • foundation model training, evaluation, and adaptation
  • protein structure modeling and docking
  • cell state prediction from large-scale perturbation datasets
  • multimodal modeling for protein function and cellular state prediction
  • familiarity with AlphaFold, RFDiffusion, CellCap, or related models for protein and cellular biology

AI Fellows will work closely with one another and with Kempner faculty, researchers, and students on foundational machine learning and biologically informed scientific applications. The position is particularly well-suited to candidates eager to apply their technical expertise in modern AI to important problems in protein biology, cellular systems, and biological intelligence.
Appointment Terms
  • Fellows will conduct research under the direction of a Kempner Institute investigator.
  • Fellows are appointed for a one-year term; reappointment may be possible for up to three consecutive years.
  • Due to the importance of in-person mentoring, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible.

Basic Qualifications
  • Bachelor's or master's degree in computer science, statistics, electrical engineering, applied mathematics, computational biology, bioengineering, biophysics, or a related quantitative field required by the expected start date.
  • Strong technical background in modern AI/ML, including deep learning and hands-on experience with frameworks such as PyTorch or JAX
  • Demonstrated research productivity, including publications in venues such as ICML, ICLR, NeurIPS, RECOMB, ISMB, or similar, and/or substantial open-source research contributions
  • Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models
  • Strong programming skills in Python and experience building and maintaining research code
  • Demonstrated ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and development workflows
  • Ability to work effectively in a collaborative research environment and communicate technical work clearly

Additional Qualifications
  • Experience with foundation model training, post-training, adaptation, or evaluation
  • Experience with protein structure modeling, protein-protein docking, or small-molecule-protein docking
  • Experience with cell state modeling from large-scale perturbation datasets, including Perturb-seq or related data
  • Experience with multimodal modeling for protein function or cellular state prediction
  • Familiarity with models and methods relevant to protein and cellular biology, including AlphaFold, RFDiffusion, CellCap, or related systems
  • Experience with large-scale datasets, distributed training, or high-performance computing environments
  • Expertise in scientific applications of AI/ML in protein biology, cellular systems, and related areas of computational biology

Special Instructions
Please submit the following items in PDF format no later than 11:59pm EST Monday, June 1, 2026:
  1. CV.
  2. A research statement of no more than 2 pages describing your experience using modern AI/ML for protein structure, cellular state, or related biological modeling problems. Please be specific about your individual contributions.
  3. References - 1-2 required
    • Please give the emails of up to 2 individuals who can describe your work and your potential for future discoveries.
    • Referees will be contacted to submit the letters directly to the Kempner Institute.
    • The application will not be considered complete until all letters have been received.
  4. Transcripts (Undergraduate and/or Master's)

Candidates selected for further consideration will be asked to submit a short video presentation reviewing their past work; additional details will be provided at that stage. Following review of the videos, a subset of candidates will be invited to interview with members of the selection committee via zoom.
Applications received after the deadline will be reviewed on a rolling basis if positions remain available.
We anticipate a start date of September 15, 2026.
Contact Information
Molly Marshall
Contact Email
Kempnerinstitute@harvard.edu
Salary Range
Expected annual salary is $54,600 for candidates holding a bachelor's degree and $60,060 for candidates holding a master's degree. Salary will be commensurate with qualifications and experience.
Minimum Number of References Required
1
Maximum Number of References Allowed
2
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