Research Jobs in Cambridge, MA
Research jobs in Cambridge, Massachusetts are in high demand, concentrated in Kendall Square, Harvard Square, and the Main Street corridor across life sciences, biotechnology, and higher education. Employers hiring right now include Harvard University, Sanofi, and Flagship Pioneering. Find a role that fits below and apply directly.
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At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.
Head of Machine Learning Research
We are seeking a scientific and technical leader to advance machine learning–enabled molecular design across our drug discovery portfolio. As a member of the Data Science & AI leadership team, you will define and deliver the models, platforms, and ways of working that shorten design–make–test–analyze cycles and improve the quality of molecules progressing toward nomination.
- Co-own the vision, roadmap, and investment case for ML-driven molecule design and multi-parameter optimization across small molecules and emerging modalities.
- Make build/buy/partner decisions across generative design, property prediction, structure-based ML, and synthesis planning; evaluate foundation models and external platforms with rigor rather than hype.
- Set the standard for how models are validated, benchmarked prospectively, and retired — including uncertainty quantification, applicability domain, and honest reporting of failure modes.
- Partner with Drug Discovery Sciences — medicinal chemistry, structural biology, biophysics, screening, DMPK, and safety — to embed ML into live programs from hit identification through candidate nomination.
- Co-own program-level design goals with chemistry leads: potency, selectivity, ADMET, developability, and IP position optimized together rather than sequentially.
- Drive active learning and closed-loop DMTA cycles, including integration with high-throughput and automated synthesis where available.
- Ensure models are delivered as reliable, supported products that chemists actually use, not one-off analyses.
- Direct development of core capabilities: ADMET and property predictors, generative and de novo design, retrosynthesis and synthetic accessibility, and structure-based ML including co-folding, pose prediction, docking rescoring, and ML-accelerated free energy methods.
- Work with data engineering to secure the assay, structural, and DMTA data foundation these models depend on — curation, provenance, harmonization across assays and sites, and feedback capture from every make-test cycle.
- Establish MLOps practice appropriate to a regulated R&D environment: versioning, reproducibility, monitoring, and documentation.
- Build, lead, and develop a team of approximately 25 spanning ML research, computational chemistry, and ML engineering; grow leaders within the group.
- Own budget, vendor relationships, and external collaborations with academic groups, consortia, and biotech partners.
- Represent the function to R&D leadership, translating technical capability into portfolio impact and translating portfolio priorities into technical strategy.
- Contribute to the broader scientific community through publication, presentation, and precompetitive collaboration where appropriate.
- PhD in computational chemistry, cheminformatics, structural biology, biophysics, computer science, or a related field, with demonstrated depth in both a molecular science and machine learning. Exceptional candidates with an MSc and equivalent depth of experience will be considered;
- Deep, current expertise across modern ML for molecules: graph neural networks, transformers, generative approaches (diffusion, flow matching, autoregressive), Bayesian optimization and active learning, transfer learning on sparse assay data, and uncertainty quantification;
- Working command of the discovery domain: SAR interpretation, multi-parameter optimization, ADMET and developability, protein structure and ligand binding, docking and free energy methods;
- Demonstrated impact on real programs — molecules advanced, cycles shortened, decisions changed. A publication record without program impact is not sufficient for this role;
- Proven ability to partner with medicinal chemists and structural biologists as scientific peers, including the credibility to challenge and be challenged on design decisions;
- Track record of delivering software or models into production use by scientists, not just prototypes.
- 12+ years of relevant experience, including 5+ years leading technical teams; experience leading leaders strongly preferred.
- Experience with modalities beyond conventional small molecules — PROTACs and molecular glues, macrocycles, peptides, covalent inhibitors, or oligonucleotides;
- Familiarity with lab automation, self-driving lab concepts, or high-throughput chemistry integration;
- Experience evaluating or deploying large-scale pretrained models for chemistry or protein structure;
- Prior experience in a large matrixed pharma R&D organization, or scaling a capability from startup to enterprise;
- Strong external profile: publications, conference presence, or leadership in precompetitive consortia.
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.
Bayer is an Equal Opportunity Employer/Disabled/Veterans
Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.
At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.
Head of Machine Learning Research
We are seeking a scientific and technical leader to advance machine learning–enabled molecular design across our drug discovery portfolio. As a member of the Data Science & AI leadership team, you will define and deliver the models, platforms, and ways of working that shorten design–make–test–analyze cycles and improve the quality of molecules progressing toward nomination.
- Co-own the vision, roadmap, and investment case for ML-driven molecule design and multi-parameter optimization across small molecules and emerging modalities.
- Make build/buy/partner decisions across generative design, property prediction, structure-based ML, and synthesis planning; evaluate foundation models and external platforms with rigor rather than hype.
- Set the standard for how models are validated, benchmarked prospectively, and retired — including uncertainty quantification, applicability domain, and honest reporting of failure modes.
- Partner with Drug Discovery Sciences — medicinal chemistry, structural biology, biophysics, screening, DMPK, and safety — to embed ML into live programs from hit identification through candidate nomination.
- Co-own program-level design goals with chemistry leads: potency, selectivity, ADMET, developability, and IP position optimized together rather than sequentially.
- Drive active learning and closed-loop DMTA cycles, including integration with high-throughput and automated synthesis where available.
- Ensure models are delivered as reliable, supported products that chemists actually use, not one-off analyses.
- Direct development of core capabilities: ADMET and property predictors, generative and de novo design, retrosynthesis and synthetic accessibility, and structure-based ML including co-folding, pose prediction, docking rescoring, and ML-accelerated free energy methods.
- Work with data engineering to secure the assay, structural, and DMTA data foundation these models depend on — curation, provenance, harmonization across assays and sites, and feedback capture from every make-test cycle.
- Establish MLOps practice appropriate to a regulated R&D environment: versioning, reproducibility, monitoring, and documentation.
- Build, lead, and develop a team of approximately 25 spanning ML research, computational chemistry, and ML engineering; grow leaders within the group.
- Own budget, vendor relationships, and external collaborations with academic groups, consortia, and biotech partners.
- Represent the function to R&D leadership, translating technical capability into portfolio impact and translating portfolio priorities into technical strategy.
- Contribute to the broader scientific community through publication, presentation, and precompetitive collaboration where appropriate.
- PhD in computational chemistry, cheminformatics, structural biology, biophysics, computer science, or a related field, with demonstrated depth in both a molecular science and machine learning. Exceptional candidates with an MSc and equivalent depth of experience will be considered;
- Deep, current expertise across modern ML for molecules: graph neural networks, transformers, generative approaches (diffusion, flow matching, autoregressive), Bayesian optimization and active learning, transfer learning on sparse assay data, and uncertainty quantification;
- Working command of the discovery domain: SAR interpretation, multi-parameter optimization, ADMET and developability, protein structure and ligand binding, docking and free energy methods;
- Demonstrated impact on real programs — molecules advanced, cycles shortened, decisions changed. A publication record without program impact is not sufficient for this role;
- Proven ability to partner with medicinal chemists and structural biologists as scientific peers, including the credibility to challenge and be challenged on design decisions;
- Track record of delivering software or models into production use by scientists, not just prototypes.
- 12+ years of relevant experience, including 5+ years leading technical teams; experience leading leaders strongly preferred.
- Experience with modalities beyond conventional small molecules — PROTACs and molecular glues, macrocycles, peptides, covalent inhibitors, or oligonucleotides;
- Familiarity with lab automation, self-driving lab concepts, or high-throughput chemistry integration;
- Experience evaluating or deploying large-scale pretrained models for chemistry or protein structure;
- Prior experience in a large matrixed pharma R&D organization, or scaling a capability from startup to enterprise;
- Strong external profile: publications, conference presence, or leadership in precompetitive consortia.
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.
Bayer is an Equal Opportunity Employer/Disabled/Veterans
Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.
See All 269+ Research Jobs in Cambridge
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Find Research JobsResearch Job Market in Cambridge
Who's Hiring
- Harvard University45
- Sanofi34
- Flagship Pioneering22
- Apple11
- Bayer11
Top Industries Hiring
- Science & Research
- Electronics & Hardware
Research Jobs in Cambridge: Frequently Asked Questions
How do I get a research job in Cambridge?
The strongest entry point in Cambridge is targeting the life sciences and biotechnology employers concentrated in Kendall Square, along with the major universities in Harvard Square and the surrounding area. Candidates who can demonstrate hands-on laboratory skills, familiarity with clinical or academic research protocols, and experience with data analysis tools stand out. Applying directly to research institutions, biotech startups, and hospital-affiliated programs gives you the best foothold in this market.
Which companies hire researchs in Cambridge?
Companies currently hiring researchs in Cambridge include Harvard University, Sanofi, and Flagship Pioneering, per current listings on Migrate Mate as of September 2026. Cambridge draws a dense mix of global pharmaceutical companies, early-stage biotech firms, and university-affiliated research centers, making it one of the most active research hiring markets in the country.
Are there remote research jobs in Cambridge?
Yes, though remote availability depends heavily on the role type, with hands-on laboratory and clinical positions requiring on-site presence while data analysis, literature review, and computational research roles are more commonly remote. About 75% of research openings tied to Cambridge are remote or hybrid as of September 2026, reflecting the mixed nature of local demand. Biotech and academic employers in Kendall Square most often offer hybrid arrangements for non-lab research functions.
How can I get a research job in Cambridge with little or no experience?
The most realistic entry path in Cambridge is pursuing a research assistant or lab technician role at one of the city's university-affiliated hospitals or academic departments, where entry-level hiring is consistent year-round. Cambridge biotech startups in Kendall Square also hire junior research associates who can demonstrate relevant coursework, internships, or volunteer lab work. Gaining experience with standard laboratory techniques or research software widely used in life sciences gives candidates a concrete edge in this market.
Which industries hire the most researchs in Cambridge?
Cambridge research roles concentrate in Science & Research and Electronics & Hardware, based on current listings on Migrate Mate as of September 2026. Cambridge's identity as a global hub for life sciences innovation, anchored by its universities and the Kendall Square biotech cluster, drives sustained demand for research professionals across those sectors.
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See All 269+ Research Jobs in Cambridge
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