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Machine Learning Postdoc Jobs in Massachusetts (NOW HIRING)

MIT Human Resources

Postdoctoral Associate

Cambridge, MA · On-site +1

POSTDOCTORAL ASSOCIATE, Mechanical Engineering, will work under the direction of Prof. Sherrie Wang ... Will develop and implement machine learning models for local weather forecasting and uncertainty ...

Worcester Polytech

Post-Doctoral Fellow

Worcester, MA

$45K - $70K/yr

The position also involves the integration of machine learning and AI-assisted approaches into materials modeling workflows. The postdoctoral researcher is expected to work independently, develop ...

NorthEastern

Postdoctoral Research Associate

Boston, MA · On-site

$60K - $85K/yr

We are seeking a postdoctoral researcher to work on quantitative ultrasound methods, focusing on the application of model-based machine learning techniques to raw ultrasound data. The project ...

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All JobsMachine Learning Postdoc JobsMachine Learning Postdoc Jobs in Massachusetts

Machine Learning Postdoc information

See Massachusetts salary details

$23.6K

$122.3K

$230.1K

How much do machine learning postdoc jobs pay per year?

As of Jul 7, 2026, the average yearly pay for machine learning postdoc in Massachusetts is $122,293.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,221.00 and $168,425.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Postdoc, you need a deep understanding of machine learning algorithms, statistical modeling, and research methodology, typically supported by a completed PhD in a related field. Proficiency with programming languages like Python or R, experience with ML libraries (e.g., TensorFlow or PyTorch), and familiarity with large-scale datasets and cloud computing platforms are important. Strong analytical thinking, effective communication, and the ability to collaborate across multidisciplinary teams are standout soft skills in this position. These qualifications ensure innovative research contributions, successful project execution, and effective dissemination of findings in both academic and applied settings.

What is a Machine Learning Postdoc job?

A Machine Learning Postdoc is a research-focused position typically held after earning a Ph.D. in a related field. It involves conducting advanced research in machine learning, developing new algorithms, and publishing in top-tier conferences and journals. Postdocs often collaborate with faculty, industry partners, and other researchers to advance the state of the art in AI. The role may include mentoring students and contributing to grant proposals. It serves as a bridge between doctoral studies and a long-term academic or industry research career.

What are the typical responsibilities and collaborative aspects of a Machine Learning Postdoc position?

A Machine Learning Postdoc typically conducts original research, develops and tests new algorithms, and contributes to academic publications or patent applications. Daily tasks often involve data analysis, model building, and experimentation using advanced computational tools. Collaboration is key in this role, as postdocs frequently work alongside faculty, graduate students, and external industry partners to advance research objectives. Additionally, they may mentor junior researchers or students, present at conferences, and participate in grant writing or project planning. This mix of independent research and team collaboration fosters both professional growth and impactful scientific advancements.

What are the most commonly searched types of Machine Learning Postdoc jobs in Massachusetts? The most popular types of Machine Learning Postdoc jobs in Massachusetts are:
What are popular job titles related to Machine Learning Postdoc jobs in Massachusetts? For Machine Learning Postdoc jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Machine Learning Postdoc jobs in Massachusetts look for? The top searched job categories for Machine Learning Postdoc jobs in Massachusetts are:
Machine Learning Postdoc jobs near you
Infographic showing various Machine Learning Postdoc job openings in Massachusetts as of July 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, 2% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $122,293 per year, or $58.8 per hour.
Postdoctoral Fellow in Biomedical Informatics (Cai Lab)

Postdoctoral Fellow in Biomedical Informatics (Cai Lab)

Harvard University

Cambridge, MA • On-site

$54K - $73K/yr

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

134th of 544 rated colleges and universities

Job description

Position
Details
Title
Postdoctoral Fellow in Biomedical Informatics (Cai Lab)
School
Harvard Medical School
Department/Area
Biomedical Informatics
Position Description
A Postdoctoral Research Fellow position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic research group focused on several synergistic goals: generating actionable Real-World Evidence (RWE) from multi-institutional Electronic Health Records (EHR), improving the generalizability of clinical evidence across diverse populations using multi-source and multi-modal data, and accelerating drug discovery by leveraging these rich, integrated datasets. This role offers a unique opportunity to develop methodological innovations that bridge the gap between computational theory and impactful clinical application.
We are seeking a highly motivated individual with a strong statistical and machine learning background. The ideal candidate will have existing expertise in several of the following areas, aligned with our research focus: 1) Causal inference, invariant learning and representation learning; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing.
Basic Qualifications
Candidates must hold a Ph.D. in a quantitative field, such as statistics, biostatistics, computer science, or a related discipline. Success in this position requires strong quantitative research capabilities and demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must possess excellent written and oral communication abilities to effectively disseminate research findings and collaborate within a multidisciplinary team.
Additional Qualifications
Special Instructions
Contact Information
Mo Moro
Contact Email
mohammed_moro@hms.harvard.edu
Salary Range
Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines
Minimum Number of References Required
Maximum Number of References Allowed
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