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Machine Learning Postdoc Jobs in Massachusetts (NOW HIRING)

The Postdoctoral Research Associate will receive professional development training, gain valuable ... Effectively design, implement, and evaluate machine learning and computational methods * Work with ...

This postdoctoral position will involve leading independent research, as well as conducting ... machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities ...

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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 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:
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 Research Associate

Postdoctoral Research Associate

NorthEastern

Boston, MA

$60K - $85K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago


Job description

About the Opportunity

Job Summary:

The Center for Drug Discovery, in association with the Bouve College of Health Sciences, Department of Pharmaceutical Sciences, and Professor Lei Xie seek to hire a Postdoctoral Research Associate to train in interdisciplinary projects involving developing new AI-driven Molecular Dynamics (MD) simulation methods and apply them to drug discovery in multiple disease areas. Preference will be given to applicants with prior training in Computer Science, Computational Biology, Computational Chemistry, and Computational Biophysics.

Extensive training opportunities cover all aspects of the drug discovery process. The Postdoctoral Research Associate will receive professional development training, gain valuable networking experience, and collaborate with scientists in The Center for Drug Discovery, Bouve College of Health Sciences, and the Institute of Experiential AI. They will also have access to personnel support, including graduate and undergraduate students, who will assist in conducting research projects. Additionally, the research scientist will have the opportunity to lead manuscript and grant writing and submit publications as the primary author.

Minimum Qualifications:

  • Ph.D. in Chemistry, Computer Science or equivalent

  • In-depth knowledge and hands-on experience in MD simulation and molecular modeling

  • Experience in processing and analyzing protein structure and chemical genomics data

  • Familiar with use of high performance computing facilities

  • Ability to communicate with experimental chemists and biologists

  • Ability to develop research plans for executing strategy, data analysis/interpretation, and presentation of results

  • Ability to work effectively in a highly integrated team environment

  • Highly collaborative, self-motivated, and team-oriented individual

  • Excellent written and oral communication skills and demonstrated ability to write peer reviewed quality work or invention disclosures for patent applications, technical reports.

  • Consistent track record of accomplishments (e.g., peer-reviewed publications and/or patents).

Key Responsibilities & Accountabilities:

Algorithm Development, Data Analysis and Communication:

  • Effectively design, implement, and evaluate machine learning and computational methods

  • Work with medicinal chemists for drug discovery projects

  • Act as key member of a multidisciplinary drug discovery project team, assisting with development of project strategy, and analysis and communication of complex data

  • Manage internal and external resources to deliver quality data in an efficient manner

  • Maintain a broad awareness of the scientific and technological landscapes of Artificial intelligence, machine learning, omics data integration, systems biology, biophysics, and drug discovery and maintain knowledge of literature related to the areas of research pursued

Scientific writing:

  • Contribute to patent, report, grant, and scientific publication writing

Training:

  • Mentor and train junior team members

Other:

  • Foster a culture of scientific excellence, teamwork, and rigorous innovation

Position Type

Research

Additional Information

Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.

Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.

Compensation Grade/Pay Type:

108S

Expected Hiring Range:

$60,315.00 - $85,192.50

With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.