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Postdoctoral Machine Learning Jobs (NOW HIRING)

... Postdoctoral Scholar to conduct research on projects in collaboration with Dr. Sanjay Srinivasan ... machine learning and multipoint geostatistics for characterization of fractures and novel ...

The Postdoctoral Scholar will join a Department of Energy (DOE)-funded project focused on the ... The core objective of this research is to advance physics-informed machine learning architectures ...

The work will involve research on machine learning, digital twins, electronic design automation ... The postdoc will have the opportunity to mentor graduate and undergraduate students. Guidance will ...

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Postdoctoral Machine Learning information

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$25K

$59K

$83.5K

How much do postdoctoral machine learning jobs pay per year?

As of Jun 4, 2026, the average yearly pay for postdoctoral 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 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 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 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 cities are hiring for Postdoctoral Machine Learning jobs? Cities with the most Postdoctoral Machine Learning job openings:
What states have the most Postdoctoral Machine Learning jobs? States with the most job openings for Postdoctoral Machine Learning jobs include:
Infographic showing various Postdoctoral Machine Learning job openings in the United States as of May 2026, with employment types broken down into 13% Locum Tenens, 25% Internship, 37% Full Time, and 25% Nights. 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 Appointee - Computational and Systems Biology

Postdoctoral Appointee - Computational and Systems Biology

Argonne National Laboratory

Lemont, IL

$70.76K - $117.93K/yr

Full-time

Posted yesterday


Job description

The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus of this role will be exploring how intrinsically disordered proteins (IDPs) mediate signaling mechanisms, with a particular emphasis on cancer therapeutics. Supported by a multi-year ARPA-H grant, this project aims to revolutionize the development of therapeutic platforms for IDPs, creating significant advancements in cancer research and treatment strategies.

As part of a collaborative initiative with the University of Chicago Comprehensive Cancer Center, the postdoctoral researcher will work closely with a multidisciplinary team of computational and experimental biologists. The team is dedicated to developing innovative therapeutic strategies for targeting IDPs, including biologics such as protein-protein inhibitors, Proteolysis-targeting chimeras (PROTACs), nanobodies, and more.

Key Responsibilities:

  • Develop foundational models to describe IDP interactions under various physiological conditions, both normal and cancer related
  • Use these models to iteratively design, validate, and refine experiments, leading to effective therapeutic strategies targeting IDPs
  • Collaborate on the development of open-source machine learning tools to support these therapeutic designs
  • Work closely with high-throughput screening teams at the University of Chicago, automating screening protocols in partnership with Argonne National Laboratory
  • Drive research at the intersection of automation, robotics, generative AI, and computational simulations, leveraging the latest advancements in computing infrastructure

Additional Responsibilities:

  • Exercise independent judgment in research activities and possess strong writing skills
  • Gain experience developing machine learning models at a world-class high-performance computing facility

The candidate will have access to state-of-the-art computing resources, including:

  • NVIDIA DGX-2 Systems: Powerful platforms for AI and deep learning (details: NVIDIA DGX-2)
  • Intel-based Aurora Supercomputer: A next-generation supercomputing system (details: Aurora Supercomputer)
  • Additional advanced compute architectures designed for machine learning and AI workflows
  • In addition to computational resources, the postdoctoral researcher will have access to dedicated wet-lab facilities at the University of Chicago and Argonne National Laboratory's Biosciences Division, allowing for seamless computational and experimental research integration

Position Requirements

  • A recent or soon to be completed PhD within the last 0-5 years
  • Computational Biology: Strong background in systems biology and regulatory network modeling
  • Interdisciplinary Collaboration: Experience working across disciplines with computational biologists, computer scientists, and experimental biologists
  • Assay Expertise: Functional understanding of quantitative and high-throughput assays, particularly in biological signaling and screening contexts
  • Machine Learning & Statistics: Proficiency in machine learning, statistical modeling, and quantitative methods for multi-omics data analysis
  • Molecular Simulations: Expertise with molecular simulation tools like OpenMM, AMBER, Gromacs, and NAMD
  • Deep Learning Development: Experience developing, validating, and deploying deep learning models, especially using Pytorch
  • Multi-Omic Data Representation: Ability to build deep representations of multi-omic data
  • Programming Proficiency: Strong knowledge of Python, C/C++, Julia, and other relevant programming languages
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full timeThe expected hiring range for this position is $70,758.00-$117,925.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.