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Ai Phd Protein Jobs (NOW HIRING)

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Computational Protein Designer

San Francisco, CA · On-site

$24.25 - $29.50/hr

You have a PhD (or equivalent industry experience) in computational biology, bioinformatics ... You have experience with generative AI. You have experience leveraging generative AI (or other ...

Weekday AI

Biology Research Scientist (BA, MS, PhD)

$50 - $70/hr

... exciting AI-driven research initiative focused on improving the accuracy of protein target ... PhD with research or industry experience in biotechnology, pharmaceutical sciences, or drug ...

Mercor

Biochemistry Research Scientist - PhD

New York, NY · On-site +1

$50 - $70/hr

About the job Mercor connects elite creative and technical talent with leading AI research labs ... Access primary sources such as papers and patents to verify protein target assignments against ...

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Ai Phd Protein information

What are the key skills and qualifications needed to thrive as an AI PhD specializing in protein research, and why are they important?

To excel as an AI PhD in protein research, you need expertise in computational biology, machine learning, and protein structure analysis, typically supported by a doctorate in a relevant field. Familiarity with programming languages like Python, deep learning frameworks (e.g., TensorFlow or PyTorch), and bioinformatics tools is crucial. Strong problem-solving abilities, collaboration, and scientific communication skills help drive innovation and interdisciplinary research. These skills are essential to develop novel AI models for protein analysis, enabling advancements in drug discovery and biological understanding.

What types of interdisciplinary collaboration are common for AI PhD professionals working in protein research?

AI PhD professionals in protein research frequently collaborate with computational biologists, bioinformaticians, structural biologists, and wet-lab experimentalists. These collaborations are essential for integrating AI-driven predictions with experimental data and biological insights. Teamwork typically involves regular meetings to discuss data findings, model interpretations, and experimental validation plans. This interdisciplinary approach not only enhances research outcomes but also provides opportunities for AI specialists to broaden their expertise and contribute to impactful scientific discoveries.

What is the difference between Ai Phd Protein vs Bioinformatics Scientist?

AspectAi Phd ProteinBioinformatics Scientist
Required CredentialsPhD in AI, Computational Biology, or related fields; expertise in machine learning and protein analysisMaster's or PhD in Bioinformatics, Computational Biology, or related fields; strong programming skills
Work EnvironmentResearch labs, biotech companies, AI-focused startupsAcademic institutions, biotech firms, healthcare organizations
Industry UsageDeveloping AI models for protein structure prediction and analysisAnalyzing biological data, developing algorithms for genomics and proteomics

While both roles involve computational analysis in biology, Ai Phd Protein focuses on applying AI and machine learning techniques specifically to protein data, whereas Bioinformatics Scientists work broadly on biological data analysis and algorithm development in genomics and proteomics.

What is an AI PhD focused on protein research?

An AI PhD focused on protein research is a doctoral program where students use artificial intelligence and machine learning techniques to study proteins. This research often involves predicting protein structures, understanding protein functions, and modeling protein interactions using computational methods. Graduates contribute to advancements in drug discovery, disease understanding, and biotechnology by leveraging AI to analyze complex biological data. The interdisciplinary nature of this field combines computer science, bioinformatics, and molecular biology.
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Infographic showing various Ai Phd Protein job openings in the United States as of July 2026, with employment types broken down into 67% Full Time, 22% Part Time, and 11% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution.
Postdoctoral AI Researcher in AI/ML for Cellular and Protein Computational Biology

Postdoctoral AI Researcher in AI/ML for Cellular and Protein Computational Biology

Harvard University

Cambridge, MA • On-site

Full-time

Posted 16 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

81st of 612 rated colleges and universities

Job description

Position
Details
Title
Postdoctoral AI Researcher in AI/ML for Cellular and Protein Computational Biology
School
Faculty of Arts and Sciences
Department/Area
Kempner Institute at Harvard University
Position Description
The Kempner Institute at Harvard University seeks early-career researchers to help shape the future of AI as Postdoctoral AI Researchers. We are looking for candidates with deep expertise in modern AI/ML and a strong record of research accomplishment who are excited 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 scholarly achievement, 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

Postdoctoral AI Researchers will work closely 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, while continuing to grow as scholars within a collaborative academic environment.
Candidates should be within 2 years of receiving their doctoral degree and will work under the direction of Kempner Institute faculty.
Appointment Terms
  • Postdoctoral AI Researchers conduct research under the general supervision of one or more Harvard faculty members.
  • The appointment is for one year; reappointment may be possible for up to a total of three years, contingent on funding, project needs, satisfactory performance, and mutual interest.
  • This is a full-time, benefits-eligible postdoctoral appointment based at the Kempner Institute at Harvard University.
  • Due to the importance of in-person mentoring and collaboration, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible.

Basic Qualifications
  • PhD in computer science, statistics, electrical engineering, applied mathematics, computational biology, bioengineering, biophysics, or a related quantitative field required by the expected start date.
  • Candidates must have received their PhD on or after September 15, 2024, or be on track to complete all PhD requirements by the expected start date of October 15, 2026.
  • Demonstrated expertise in modern AI/ML, including deep learning and hands-on experience with frameworks such as PyTorch or JAX.
  • Strong publication record in leading venues such as ICML, ICLR, NeurIPS, RECOMB, ISMB, or comparable conferences and journals, 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.
  • Experience in computational biology, biological data analysis, protein modeling, cellular modeling, or related areas.
  • 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 8, 2026:
  • CV
  • 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.
  • References - 2-3 required
    • Please give the emails of up to 3 individuals who can describe your previous related work.
    • 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.

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 October 15, 2026.
Contact Information
Molly Marshall
Contact Email
KempnerInstitute@Harvard.edu
Salary Range
Expected salary is $100,000, subject to compliance with the applicable salary requirements for the appointment. This is a benefits eligible position.
Minimum Number of References Required
2
Maximum Number of References Allowed
3
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