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Temporary Machine Learning Postdoc Jobs in Chicago, IL

Evozyne

Applied AI Research Fellow

Chicago, IL · On-site +1

Late-stage PhD student or postdoc in a quantitative or computational field * Hands-on experience ... Familiarity with modern machine learning approaches (e.g., deep learning, generative models, or ...

Evozyne

Applied AI Research Fellow

Chicago, IL · On-site +1

Late-stage PhD student or postdoc in a quantitative or computational field * Hands-on experience ... Familiarity with modern machine learning approaches (e.g., deep learning, generative models, or ...

EVOZYNE INC

Applied AI Research Fellow

Chicago, IL · On-site

Late-stage PhD student or postdoc in a quantitative or computational field * Hands-on experience ... Familiarity with modern machine learning approaches (e.g., deep learning, generative models, or ...

Aerotek

Machine Builder

Crystal Lake, IL · On-site

$23 - $28/hr

... learning and professional growth. Work Environment The role is based in a large equipment ... If eligible, the benefits available for this temporary role may include the following: * Medical ...

Socket.dev

Senior Data Scientist

Chicago, IL · On-site

$89 - $127/hr

Applying quantitative techniques, including statistical and machine learning, to uncover latent ... Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan ...

UNAVAILABLE

Senior Data Scientist

Chicago, IL · On-site

$89 - $127/hr

Applying quantitative techniques, including statistical and machine learning, to uncover latent ... Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan ...

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Temporary Machine Learning Postdoc information

What is a temporary machine learning postdoc?

A Temporary Machine Learning Postdoc is a fixed-term research position, typically held at a university or research institution, focused on advancing knowledge and techniques in machine learning. Postdoctoral researchers in this role work on specific projects, often collaborating with faculty, graduate students, or industry partners. The position is designed to provide advanced training and research experience after earning a PhD, usually lasting from several months to a couple of years. Temporary postdocs may contribute to publishing academic papers, developing algorithms, and mentoring students, while preparing for longer-term academic or industry careers.

What skills and qualifications are needed to thrive as a temporary machine learning postdoc?

To thrive as a Temporary Machine Learning Postdoc, you need a PhD in a relevant field, a solid grasp of machine learning theory, and strong programming skills (often in Python or R). Experience with tools such as TensorFlow, PyTorch, and high-performance computing environments, as well as a record of peer-reviewed research, is typically required. Strong analytical thinking, collaboration, and effective communication help you stand out in this research-intensive role. These skills are essential for advancing cutting-edge research, publishing impactful findings, and contributing to interdisciplinary projects.

What types of projects and collaborations can a temporary machine learning postdoc expect to engage in?

A Temporary Machine Learning Postdoc typically works on cutting-edge research projects, often contributing to ongoing studies or initiating novel investigations within the field. Collaboration is common, both within their immediate research group and with interdisciplinary teams, such as data scientists, domain experts, or industry partners. Postdocs may also mentor graduate students, present findings at conferences, and publish papers, gaining valuable experience that can lead to academic or industry roles. The environment is fast-paced and research-driven, offering opportunities for professional growth and expanding one's research portfolio.

What is the difference between Temporary Machine Learning Postdoc vs Data Scientist?

AspectTemporary Machine Learning PostdocData Scientist
CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often requires experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research centersBusiness, technology, finance, healthcare
Search & Comparison IntentUnderstanding research-focused roles, academic opportunitiesIndustry roles, applied data analysis, business impact

The Temporary Machine Learning Postdoc is primarily research-oriented, often in academic or research settings, requiring a PhD. In contrast, a Data Scientist typically works in industry, applying data analysis and machine learning to solve business problems, often with a Bachelor's or Master's degree. Both roles involve machine learning skills but differ in environment, focus, and experience level.

What are the most commonly searched types of Machine Learning Postdoc jobs in Chicago, IL?

The most popular types of Machine Learning Postdoc jobs in Chicago, IL are:

What are popular job titles related to Temporary Machine Learning Postdoc jobs in Chicago, IL?

For Temporary Machine Learning Postdoc jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Temporary Machine Learning Postdoc jobs in Chicago, IL look for?

The top searched job categories for Temporary Machine Learning Postdoc jobs in Chicago, IL are:

Temporary Machine Learning Postdoc jobs near you

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

Argonne National Laboratory

Lemont, IL • On-site

$72K - $121K/yr

Full-time

Re-posted 11 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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