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Postdoctoral Fellow Machine Learning Jobs in Illinois

University of Utah

Post Doc Res Assoc

Campus, IL

$65K - $73K/yr

Building on our leadership in microprotein discovery and function, we are now expanding in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to ...

University of Utah

Post Doc Res Assoc

Campus, IL · On-site

$65K - $73K/yr

Building on our leadership in microprotein discovery and function, we are now expanding in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to ...

University of Utah

Post Doc Res Assoc

Campus, IL · On-site

$65K - $73K/yr

Building on our leadership in microprotein discovery and function, we are now expanding in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to ...

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Postdoctoral Fellow Machine Learning information

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.

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 are popular job titles related to Postdoctoral Fellow Machine Learning jobs in Illinois? For Postdoctoral Fellow Machine Learning jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Postdoctoral Fellow Machine Learning jobs in Illinois look for? The top searched job categories for Postdoctoral Fellow Machine Learning jobs in Illinois are:
What cities in Illinois are hiring for Postdoctoral Fellow Machine Learning jobs? Cities in Illinois with the most Postdoctoral Fellow Machine Learning job openings:
Postdoctoral Fellow Machine Learning jobs near you
Infographic showing various Postdoctoral Fellow Machine Learning job openings in Illinois as of July 2026, with employment types broken down into 80% Full Time, 18% Part Time, 1% Temporary, and 1% Contract. Highlights an 91% Physical, and 9% Remote job distribution.
Postdoctoral Appointee - Building Agentic AI Platform for X-ray Science

Postdoctoral Appointee - Building Agentic AI Platform for X-ray Science

Argonne National Laboratory

Lemont, IL

$72K - $121K/yr

Full-time

Posted 6 days ago

Job description

We are seeking a highly motivated and creative Postdoctoral Researcher to join the X-ray Science Division (XSD) at Argonne National Laboratory. The successful candidate will develop an AI-enabled platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher will work with a multidisciplinary team to advance agentic AI tools for simulation, interpretation, data analysis, and scientific discovery. The appointment is expected to last two years and the contract is extended yearly.

Position Requirements

  • A recent PhD (within 5 years) in computational chemistry, chemistry, materials science, physics, computational science, computer science, engineering, or a related field.

  • Strong computational chemistry background in atomistic simulations, electronic-structure theory, DFT, structure-property relationships, and interpretation of simulation results.

  • Hands-on experience with DFT or electronic-structure codes such as VASP, Quantum ESPRESSO, CP2K, ABINIT, GPAW, Gaussian, ORCA, Q-Chem, or related packages.

  • Strong materials science or chemistry domain knowledge, such as bonding, defects, catalysis, batteries, solid-state chemistry, molecular systems, or related materials classes.

  • Strong Python skills and familiarity with LLM APIs, agent frameworks , PyTorch, and the Python scientific stack (e.g., numpy, pandas, scikit-learn). Passion for front-end development and web-based applications, back-end services and API design (e.g., FastAPI, Flask), and deploying applications in local or cloud environments.

  • Experience with complex scientific datasets and reproducible analysis or simulation workflows.

  • Effective written and oral communications skills.

  • Demonstrated ability to work both independently and collaboratively in a multidisciplinary environment.

  • Commitment to Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork.

Preferred Knowledge, Skills, and Experience

  • Experience with X-ray absorption spectroscopy theory, modelling, and interpretation, including XANES/EXAFS.

  • Hands-on experience with XAS simulation packages such as FEFF, OCEAN, FDMNES, XSpectra, or exciting.

  • Experience comparing simulated and experimental XAS/XAFS spectra.

  • Experience with high-throughput spectroscopy workflows, HPC, synchrotron datasets, or physics-informed AI.

**Please include a cover letterthat briefly describes relevant simulation, chemistry, AI/ML, and XAS experience; include code links if available.**

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full timeThe expected hiring range for this position is $72,879.00-$121,465.00.

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.

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