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Postdoctoral Machine Learning Jobs in Boston, MA

NorthEastern

Postdoctoral Research Associate

Boston, MA

$60K - $85K/yr

... postdoctoral researcher to start as soon as possible. The research focus will be on developing and ... Coding and/or machine learning experiences are highly valued. Specific projects may involve ...

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 ...

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Postdoctoral Machine Learning information

See Boston, MA salary details

$27.2K

$64.1K

$90.7K

How much do postdoctoral machine learning jobs pay per year?

As of Jun 9, 2026, the average yearly pay for postdoctoral machine learning in Boston, MA is $64,121.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,200.00 and $72,200.00 per year, depending on experience, location, and employer.

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

To thrive as a Postdoctoral Machine Learning researcher, you need a strong background in machine learning theory, statistical analysis, and programming, typically supported by a Ph.D. in computer science, engineering, or a related quantitative field. Experience with Python, TensorFlow, PyTorch, and advanced data analytics tools is highly valued, as are relevant publications and experience with version control systems like Git. Strong problem-solving abilities, clear communication skills, and effective teamwork are crucial to excel in collaborative research settings. These skills and qualities are essential to drive innovative research, efficiently navigate complex datasets, and contribute to impactful scientific discoveries.

What is a Postdoctoral Machine Learning job?

A Postdoctoral Machine Learning job is a research-focused position for individuals who have recently earned a Ph.D. in machine learning, artificial intelligence, or a related field. It typically involves conducting advanced research, publishing papers, collaborating with academic or industry partners, and developing novel algorithms or models. These roles are often hosted by universities, research institutes, or tech companies. The position helps researchers gain additional expertise and contribute to cutting-edge advancements before transitioning to faculty, industry, or independent research roles.

What are the typical daily responsibilities of a Postdoctoral Machine Learning researcher?

A Postdoctoral Machine Learning researcher typically spends their day designing and implementing machine learning algorithms, analyzing experimental results, and preparing manuscripts for publication. They often collaborate with interdisciplinary teams of scientists and engineers, attend lab meetings, and contribute to grant writing or project proposals. Regular activities also include keeping up with recent scientific literature, mentoring graduate or undergraduate students, and presenting research findings at conferences or seminars. The blend of technical development and scientific communication makes each day dynamic and offers opportunities to influence both academia and industry.

What are popular job titles related to Postdoctoral Machine Learning jobs in Boston, MA? For Postdoctoral Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Postdoctoral Machine Learning jobs in Boston, MA look for? The top searched job categories for Postdoctoral Machine Learning jobs in Boston, MA are:
Postdoctoral Machine Learning jobs near you
Postdoctoral Fellow in Geometric Machine Learning

Postdoctoral Fellow in Geometric Machine Learning

Harvard University

Cambridge, MA • On-site

$67K - $91K/yr

Full-time

Posted 23 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
Postdoctoral Fellow in Geometric Machine Learning
School
Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area
Applied Math
Position Description
A postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences.
This is a one-year position with the possibility of extension.
For more details on our research and recent publications, see the Geometric Machine Learning Group's website: https://weber.seas.harvard.edu
For questions, please email mweber@seas.harvard.edu .
Applications will be reviewed on a rolling basis.
Basic Qualifications
A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment.
Additional Qualifications
Special Instructions
To apply, please submit the following materials:
  1. CV
  2. Research Statement outlining your current and future research interests
  3. Three Reference Letters
  4. Copies of two publications representative of your work and research interest

SEAS is dedicated to building a diverse and welcoming community.
Contact Information
For more details on our research and recent publications, see the Geometric Machine Learning Group's website: https://weber.seas.harvard.edu
Contact Email
mweber@seas.harvard.edu
Salary Range
$67,600 - $91,826
Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.
Minimum Number of References Required
3
Maximum Number of References Allowed
3
Keywords

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