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Temporary Machine Learning Postdoc Jobs in Chicago, IL

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Temporary Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Postdoc, and why are they important?

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 during their appointment?

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 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 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:
Postdoctoral Appointee - Computational and Systems Biology

Postdoctoral Appointee - Computational and Systems Biology

Argonne National Laboratory

Lemont, IL

$70K - $117K/yr

Full-time

Posted 18 days ago


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.