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Postdoctoral Fellow Machine Learning Jobs (NOW HIRING)

Mount Sinai Hospital

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$72K - $80K/yr

This Postdoctoral Research Fellowship position will focus primarily on using biomedical data science and machine learning methodologies to explore cardiovascular disease phenotypes in the Mount Sinai ...

Johns Hopkins University

Postdoctoral Fellow

Baltimore, MD · On-site

$48K - $66K/yr

Machine learning / artificial intelligence (using imaging or 'omics data) Responsibilities: * Lead ... Postdoctoral fellows receive comprehensive benefits; see JHU Postdoctoral Fellow Benefits Overview ...

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How much do postdoctoral fellow machine learning jobs pay per year?

As of Jun 4, 2026, the average yearly pay for postdoctoral fellow machine learning in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Postdoctoral Fellow in Machine Learning, you need a strong background in computer science, mathematics, and statistics, typically supported by a PhD and relevant research experience. Familiarity with programming languages such as Python, machine learning frameworks like TensorFlow or PyTorch, and experience in high-performance computing environments are commonly required. Strong analytical thinking, effective scientific communication, and collaboration skills help you contribute to research teams and disseminate findings. These skills and qualities are crucial for advancing research, developing innovative solutions, and building a successful academic or industry career in machine learning.

What are some common challenges faced by Postdoctoral Fellows in Machine Learning, and how can they be addressed?

Postdoctoral Fellows in Machine Learning often encounter challenges such as balancing independent research with collaborative projects, staying current with rapidly evolving technologies, and securing funding or publishing in top-tier journals. To address these, it's helpful to establish clear communication with mentors and collaborators, set aside dedicated time for reading recent literature, and actively seek feedback on research drafts. Building a professional network through conferences and seminars can also open opportunities for collaboration and career advancement.

What is a Postdoctoral Fellow in Machine Learning?

A Postdoctoral Fellow in Machine Learning is a researcher who has recently completed their PhD and is engaged in advanced research in the field of machine learning. This role typically involves conducting independent or collaborative research, publishing scientific papers, and sometimes mentoring students. Postdoctoral fellows often work at universities, research institutes, or industry labs, focusing on developing new algorithms, improving existing models, or applying machine learning techniques to specific problems. The position is usually temporary, lasting one to three years, and aims to prepare researchers for permanent academic or industry roles.

What is the difference between Postdoctoral Fellow Machine Learning vs Postdoctoral Research Scientist?

AspectPostdoctoral Fellow Machine LearningPostdoctoral Research Scientist
Required credentialsPhD in Computer Science, Data Science, or related fieldPhD in relevant field, often with specialized research experience
Work environmentAcademic labs, universities, research institutionsResearch labs, industry R&D departments, tech companies
Employer and industry usagePrimarily academia, government researchPrimarily industry, corporate research divisions
Common search and comparison intentUnderstanding academic research roles in machine learningExploring industry-focused research career paths

Postdoctoral Fellow Machine Learning roles typically focus on academic research, requiring a PhD and working in universities or research institutions. In contrast, Postdoctoral Research Scientist positions are often industry-based, emphasizing applied research within corporate R&D departments. Both roles involve advanced machine learning expertise but differ mainly in work environment and career trajectory.

More about Postdoctoral Fellow Machine Learning jobs
What cities are hiring for Postdoctoral Fellow Machine Learning jobs? Cities with the most Postdoctoral Fellow Machine Learning job openings:
What states have the most Postdoctoral Fellow Machine Learning jobs? States with the most job openings for Postdoctoral Fellow Machine Learning jobs include:
What job categories do people searching Postdoctoral Fellow Machine Learning jobs look for? The top searched job categories for Postdoctoral Fellow Machine Learning jobs are:
Postdoctoral Fellow Machine Learning jobs near you
Infographic showing various Postdoctoral Fellow Machine Learning job openings in the United States as of May 2026, with employment types broken down into 30% Full Time, and 70% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.
Postdoctoral Fellow in Geometric Machine Learning

Postdoctoral Fellow in Geometric Machine Learning

Harvard University

Cambridge, MA • On-site

$67K - $91K/yr

Full-time

Posted 19 days ago

Harvard University rating

8.1

Company rating: 8.1 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

130th of 532 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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