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Junior Python Developer Jobs

Argonne National Laboratory

Altom Transport

Cleveland-Cliffs

Onsite

<p>Location: Burns Harbor, IN</p><p></p><p>The Information Technology department currently has an opportunity in Applications Development onsite in the locations of Burns Harbor, Indiana or East Chicago, Indiana. Cleveland-Cliffs Inc. offers challenging careers in Information Technology for people with leadership, technical, and interpersonal skills.</p><p></p><p><b>Summary of Responsibilities</b></p><ul><li><p>Learn, support, and help maintain the PSImetals Manufacturing Execution System (MES)</p></li><li><p>Assist in developing and configuring MES functionality, including custom logic, interfaces, and system extensions.</p></li><li><p>Troubleshoot system issues by gathering information, analyzing logs, and working with senior team members to identify and implement long‑term fixes.</p></li><li><p>Participate in testing activities, including functional tests, integration tests, and regression tests for MES enhancements and upgrades.</p></li><li><p>Support ongoing system stability by monitoring MES jobs, interfaces, and data flows.</p></li><li><p>Assist in integrating PSImetals components with databases, automation systems, and enterprise applications (e.g., ERP).</p></li><li><p>Work closely with operations, process engineers, and IT teams to understand requirements and translate them into working capabilities.</p></li><li><p>Help document technical processes, support procedures, and configuration details to ensure maintainability and knowledge transfer.</p></li><li><p>Develop foundational knowledge of manufacturing processes and how MES applications support operational execution.</p></li><li><p>Other duties as assigned.</p></li></ul><p></p><p><b>Minimum Qualifications</b></p><ul><li><p>Associate degree in Information Technology, Computer Science, or a related technical field (or equivalent coursework demonstrating a strong technical foundation).</p></li><li><p>Clear, confident verbal and written communication skills suitable for working with both technical and operations personnel.</p></li><li><p>Strong organizational skills with the ability to manage multiple tasks in a fast‑paced environment.</p></li><li><p>Classroom, project, or internship exposure to object‑oriented programming (e.g., C#, Java, or similar).</p></li><li><p>Basic understanding of relational databases or SQL.</p></li><li><p>Enthusiasm to learn complex manufacturing systems and support MES environments.</p></li><li><p>Interest in troubleshooting technical issues and developing problem‑solving skills.</p></li><li><p>Must work on‑site, 5 days per week, in a production‑focused environment.</p></li></ul><p></p><p><b>Preferred Qualifications</b></p><ul><li><p>Bachelor’s degree in Information Technology, Computer Science, Software Engineering, or a related field.</p></li><li><p>Exposure to or project experience with manufacturing systems, or MES concepts (coursework or internship acceptable).</p></li><li><p>Knowledge of software development practices such as version control (Git), Agile methodologies, or basic CI/CD concepts.</p></li><li><p>Experience working with APIs, system integrations, or data exchange formats (REST, XML, JSON).</p></li><li><p>Familiarity with scripting or programming languages used in integration or system logic (e.g., C#, Java, Python).</p></li><li><p>Understanding data structures, basic networking, or system architecture concepts.</p></li><li><p>Demonstrated interest in manufacturing, industrial technology, or real‑time systems.</p></li><li><p>Curiosity, eagerness to learn, and the ability to colla.</p></li></ul><p></p><p>Cleveland-Cliffs Inc. is the largest flat-rolled steel company and the largest iron ore pellet producer in North America. The Company is vertically integrated from mined raw materials, direct reduced iron, and ferrous scrap to primary steelmaking and downstream finishing, stamping, tooling, and tubing. We offer an excellent total compensation package including competitive pay with variable compensation opportunity, health insurance, retirement plan, education assistance, paid time off, and more. </p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><i>Cleveland-Cliffs Inc. is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the employment process, please send an e-mail to <a target="_blank" href="mailto:careers&#64;clevelandcliffs.com"><span class="WGU2">careers&#64;clevelandcliffs.com</span></a> or call 1-(312) 899-3097 and let us know the nature of your request and your contact information. Do not email your application materials to this email address. Application materials sent to this email address will not be considered.</i></p><p style="text-align:inherit"></p><p style="text-align:left"><i>Cleveland-Cliffs Inc. is an equal opportunity employer – <span class="WGU2">M/F/Veteran/Disability.</span> <span>We are a drug-free workplace and conduct pre-employment screening as a condition of employment.</span></i></p>

Associate IT Applications Engineer

IT Applications Engineer

Associate degree in IT or related field; strong communication; programming exposure; basic SQL; on-site 5 days/week; interest in MES and manufacturing systems.

<p><strong>Duration:</strong> Summer 2026 (Flexible start and end dates)<br /> <strong>Hours:</strong> 40 hours per week (depending on availability)<br /> <strong>Paid Internship</strong></p><h3>About Us:</h3><p>Altom Transport is a premier petrochemical and hazardous materials carrier committed to safety, innovation, and operational excellence. We're looking for a <strong>Software Development Intern</strong> to help support our operations, billing, and app development initiatives. This is a great opportunity for students or recent graduates looking to gain real-world experience in software development within the transportation and logistics industry.</p><p><em>This position operates out of our Hammond terminal.</em></p>

Summer 2026 Software Development Intern

Software Development Intern

Current student or recent graduate in Computer Science or Software Engineering; experience with JavaScript/Python; knowledge of SQL/NoSQL databases; familiarity with cloud platforms (AWS/Azure/Google Cloud); able to work independently and in a team; strong problem-solving skills.

Argonne

<p>The Industrial Technologies Group within the Energy Systems and Infrastructure Assessment (ESIA) Division at Argonne National Laboratory seeks a highly qualified Postdoctoral Appointee to conduct applied research on AI-driven and AI-enhanced industrial energy systems optimization modeling, material flow analysis, and supply chain analysis of industrial commodities and critical materials.</p><p></p><p>The successful candidate will contribute to Argonne’s industrial capacity planning, logistics optimization, and supply chain analysis models and apply these tools to support high-impact research on resilient, competitive, and energy-efficient U.S. manufacturing systems. The appointee will be expected to lead core model development and as needed, help expand capabilities in co-optimization of industrial end-use and energy supply systems, multi-objective and stochastic optimization, advanced statistical analysis, and data visualization.</p><p></p><p>This position offers the opportunity to work with a multidisciplinary team of computational scientists, economists, engineers, and other researchers to develop data-driven, decision-relevant analytical tools for complex industrial systems.</p><p></p><p>Key Responsibilities:</p><ul><li><p>Develop, improve, and apply computational models for industrial capacity planning, logistics optimization, material flow analysis, and supply chain analysis.</p></li><li><p>Apply artificial intelligence, machine learning, LLMs, and advanced statistical techniques to industrial energy systems, manufacturing systems, and commodity supply chains.</p></li><li><p>Integrate data-driven methods with optimization-based modeling frameworks, including linear, mixed-integer, stochastic, robust, and multi-objective optimization.</p></li><li><p>Conduct analyses of industrial system resilience, competitiveness, and operational performance under uncertainty.</p></li><li><p>Support model development for co-optimization of industrial end-use systems and energy supply systems.</p></li><li><p>Build reproducible computational workflows for data processing, model development, calibration, validation, and scenario analysis.</p></li><li><p>Develop visualization and decision-support tools to communicate results to technical and non-technical audiences.</p></li><li><p>Publish research in peer-reviewed journals, contribute to sponsor reports and technical deliverables, and present work to collaborators and stakeholders.</p></li><li><p>Collaborate effectively with interdisciplinary teams across Argonne and with external partners.</p></li></ul><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Position Requirements</b></p><ul><li><p>Recent or soon-to-be-completed Ph.D. (typically completed within the last 0-5 years) in computer science, applied mathematics, operations research, engineering, economics, or a related quantitative field.</p></li><li><p>Demonstrated expertise in AI, machine learning, statistical modeling, or advanced analytics applied to complex industrial, energy, logistics, manufacturing, or supply chain systems.</p></li><li><p>Experience developing and applying optimization models, such as linear programming, mixed-integer programming, nonlinear optimization, stochastic optimization, robust optimization, or multi-objective optimization.</p></li><li><p>Experience integrating machine learning or data-driven methods with optimization and decision-support models.</p></li><li><p>Background in one or more of the following: time-series analysis, neural networks, forecasting, uncertainty quantification, sensitivity analysis, surrogate modeling, clustering, anomaly detection, or probabilistic modeling.</p></li><li><p>Proficiency in Python/Julia/R and scientific computing/data analysis tools and related libraries.</p></li><li><p>Experience working with large, heterogeneous datasets and developing reproducible analytical workflows, including using LLMs for the same.</p></li><li><p>Demonstrated software development practices, including documentation and version control.</p></li><li><p>Skilled in written and oral communication, with the ability to explain technical methods and findings to multidisciplinary audiences.</p></li><li><p>Ability to work both independently and collaboratively in a team-based research environment.</p></li><li><p>Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.</p></li><li><p>This position requires an on-site presence at the Argonne campus in Lemont, Illinois.</p></li><li><p>US citizenship: To perform the essential functions of this position successful applicants must provide proof of U.S. citizenship, which is required to comply with federal regulations and contract.</p></li></ul><p></p><p>Preferred Qualifications:</p><ul><li><p>Experience applying AI/ML or advanced analytics to industrial energy systems, manufacturing systems, material flow analysis, or commodity supply chain analysis.</p></li><li><p>Experience with supply chain network modeling, logistics analysis, infrastructure systems analysis, or resilience and disruption modeling.</p></li><li><p>Familiarity with hybrid mechanistic-data-driven modeling, surrogate-assisted optimization, or digital twin methods.</p></li><li><p>Experience with Bayesian methods, graph/network analytics, reinforcement learning, or other advanced AI approaches relevant to industrial systems.</p></li><li><p>Experience with geospatial analysis, spatial data integration, or network-based modeling of infrastructure or industrial systems.</p></li><li><p>Familiarity with high-performance computing, cloud computing, or parallel computing environments for training models and solving optimization problems.</p></li><li><p>Experience developing dashboards, visual analytics tools, or decision-support interfaces.</p></li><li><p>Strong record of peer-reviewed publications and demonstrated ability to lead technical research tasks.</p></li><li><p>Interest in applied research that informs industrial competitiveness, energy systems, manufacturing policy, and supply chain resilience.</p></li></ul><p></p><p>This position description documents the general nature and level of work but is not intended to be a comprehensive list of all activities, duties and responsibilities required of job incumbent. Consequently, job incumbent may be required to perform other duties as assigned.</p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Family</b></p>Postdoctoral<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Profile</b></p>Postdoctoral Appointee<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Worker Type</b></p>Long-Term (Fixed Term)<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Time Type</b></p>Full time<p style="text-align:inherit"></p><p style="text-align:inherit"></p><h3></h3>The expected hiring range for this position is $72,879.00-$121,465.00.<h3></h3><p style="text-align:inherit"></p><p style="text-align:left"><span><span>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. </span></span></p><p style="text-align:inherit"></p><p style="text-align:left">Click <a target="_blank" href="https://www.anl.gov/hr/healthcare-insurance"><span><u>here</u></span></a> to view Argonne employee benefits!</p><h3></h3><p style="text-align:inherit"></p><p><i><span>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.</span></i></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p style="text-align:left"><i>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&#39;s Legal Department.  </i></p><p style="text-align:inherit"></p><p style="text-align:left"><i>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.</i></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Postdoctoral Appointee: AI-Driven Industrial Energy Systems and Supply Chain Modeling

Postdoctoral Appointee

PhD in a quantitative field; expertise in AI/ML, optimization, and data-driven modeling; Python/Julia/R; experience with large datasets and reproducible workflows; strong communication.

<p>The Materials Science Division is seeking applicants for a Postdoctoral Appointee who will conduct cutting-edge research in AI for Materials Chemistry, with a focus on energy storage and conversion. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence. The project involves: </p><p><br />1. Quantum Mechanical Calculations:  <br />   - Performing first-principles based or Density Functional Theory (DFT) calculations for molecules/materials and interphases<br />   - Utilizing Molecular Dynamics (MD) simulations to study chemical transformations in materials.  <br />2. Artificial Intelligence Applications:  <br />   - Leveraging conventional machine learning techniques for materials property prediction and Bayesian approaches<br />   - Exploring Foundational Models and Agentic AI to address challenges in energy storage and conversion. </p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Position Requirements</b></p><p>Candidates must meet the following qualifications:  <br />1. Educational Background:  <br />   - A recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Computational Materials Science, Chemical Engineering or a closely related field.  <br />2. Technical Expertise:  <br />   - Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics.  <br />   - Experience with High-Performance Computing (HPC) systems and intelligent workflows.  <br />3. Programming Skills:  <br />   - Proficiency in C&#43;&#43;/or Python programming languages is essential.  </p><p>4. Research Contributions:  <br />   - Demonstrated publications in AI for Materials Chemistry.  <br />5. Collaboration and Communication:  <br />   - Willingness to work on multiple projects and collaborate effectively with interdisciplinary teams.  <br />   - Strong written and oral communication skills.  <br />6. Core Values:  <br />   - Ability to model Argonne’s core values: impact, safety, respect, integrity, and teamwork.  </p><p></p><p>Preferred Qualifications  <br />- Experience in integrating AI techniques with quantum mechanical calculations.  <br />- Familiarity with recent advancements in Foundational Models and Agentic AI.  <br /> </p><p></p><p><b>Please upload the following as attachments to your application via Workday:</b></p><ul><li><p>CV/Resume</p></li><li><p>Unofficial Ph.D. Transcripts</p></li><li><p>If already awarded, a copy of your Ph.D. diploma. Candidates can be currently enrolled to apply, but must have proof of degree conferral by the position start date.</p></li></ul><p></p><p>At the point of interview, candidates will be asked to submit the name/contact of three references.</p><p></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Family</b></p>Postdoctoral<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Profile</b></p>Postdoctoral Appointee<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Worker Type</b></p>Long-Term (Fixed Term)<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Time Type</b></p>Full time<p style="text-align:inherit"></p><p style="text-align:inherit"></p><h3></h3>The expected hiring range for this position is $72,879.00-$121,465.00.<h3></h3><p style="text-align:inherit"></p><p style="text-align:left"><span><span>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. </span></span></p><p style="text-align:inherit"></p><p style="text-align:left">Click <a target="_blank" href="https://www.anl.gov/hr/healthcare-insurance"><span><u>here</u></span></a> to view Argonne employee benefits!</p><h3></h3><p style="text-align:inherit"></p><p><i><span>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.</span></i></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p style="text-align:left"><i>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&#39;s Legal Department.  </i></p><p style="text-align:inherit"></p><p style="text-align:left"><i>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.</i></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Postdoctoral Appointee - MSD AI for Materials Chemistry

PhD in Materials Science or related field; computational materials science, HPC, Python/C++; AI for materials chemistry publications; strong collaboration and communication; alignment with Argonne values.

<p></p><p>The AMO Physics group within Argonne’s Chemical Sciences and Engineering Division (CSE) invites applications for a Postdoctoral Appointee position. Our research investigates fundamental x-ray and optical interactions with atoms and molecules in gases, clusters, and liquids, providing a scientific foundation for Department of Energy–relevant applications.</p><p></p><p>This appointment will emphasize theoretical modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development and application of nonlinear x-ray spectroscopies. The successful candidate will work closely with experimental collaborators conducting measurements at large-scale x-ray user facilities, including synchrotrons and x-ray free-electron lasers.</p><p></p><p><u>Key Responsibilities</u></p><ul><li><p>Perform electronic-structure calculations using ab initio quantum chemistry methods and software (commonly CASSCF-based approaches)</p></li><li><p>Investigate a range of molecular systems, including:</p><ul><li><p>Transition-metal complexes (e.g., chiral ruthenium and iridium complexes)</p></li><li><p>Local and nonlocal inner-shell decay processes in solvated ions and transition-metal complexes</p></li><li><p>Small gas-phase molecules and organic chiral compounds</p></li></ul></li></ul><ul><li><p>Compute accurate transition moments beyond the electric-dipole approximation and simulate x-ray observables, including x-ray absorption, x-ray scattering, x-ray circular dichroism, photoelectron spectra, and nonlinear x-ray signals</p></li><li><p>Model ultrafast molecular dynamics using time-resolved observables, including numerical solutions of the time-dependent Schrödinger equation and classical molecular dynamics techniques</p></li><li><p>Publish results in peer-reviewed journals and present findings at scientific conferences</p></li><li><p>Engage in collaborative research across Argonne and with external partners</p></li></ul><p></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Position Requirements</b></p><p></p><ul><li><p>Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics, chemistry, or physical chemistry</p></li><li><p>Demonstrated expertise in theoretical quantum chemistry and experience with quantum chemistry packages (e.g., Molpro, NWChem)</p></li><li><p>Strong skills in developing and implementing computational and numerical methods; familiarity with parallel computing on CPU/GPU architecture is desirable</p></li><li><p>Proficiency in Python for computing observables and analyzing quantum chemistry outputs</p></li><li><p>Interest in ultrafast x-ray science and synchrotron/FEL sources, with a focus on theoretical frameworks that enable interpretation of experimental measurements</p></li><li><p>Excellent written and oral communication skills, including the ability to prepare publications and technical reports</p></li><li><p>Ability to work independently and effectively as part of a multidisciplinary research team</p></li><li><p>Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork</p></li></ul><p></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Family</b></p>Postdoctoral<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Profile</b></p>Postdoctoral Appointee<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Worker Type</b></p>Long-Term (Fixed Term)<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Time Type</b></p>Full time<p style="text-align:inherit"></p><p style="text-align:inherit"></p><h3></h3>The expected hiring range for this position is $72,879.00-$121,465.00.<h3></h3><p style="text-align:inherit"></p><p style="text-align:left"><span><span>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. </span></span></p><p style="text-align:inherit"></p><p style="text-align:left">Click <a target="_blank" href="https://www.anl.gov/hr/healthcare-insurance"><span><u>here</u></span></a> to view Argonne employee benefits!</p><h3></h3><p style="text-align:inherit"></p><p><i><span>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.</span></i></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p style="text-align:left"><i>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&#39;s Legal Department.  </i></p><p style="text-align:inherit"></p><p style="text-align:left"><i>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.</i></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Postdoctoral Appointee – Computational Quantum Chemistry for X-ray Spectroscopies

Recent or soon-to-be-completed PhD in physics, chemistry, or physical chemistry; expertise in theoretical quantum chemistry; proficiency in Python; experience with quantum chemistry packages; ability to work independently in a multidisciplinary team.

<p>The Energy Systems and Infrastructure Assessment Division at Argonne National Laboratory is seeking a highly motivated Postdoctoral Appointee to support research on AI-enabled monitoring, control, and cyber-resilient operation of distribution systems and networked microgrids. The successful candidate will contribute primarily to the control and cybersecurity thrusts of a multi-institutional project focused on AI-enabled resilient operation of distribution systems and networked microgrids under uncertainty, disturbances, and cyber-physical threats.</p><p></p><p>This position is best suited for a candidate with strong expertise in machine learning for cyber-physical systems and a solid understanding of electric power distribution systems, and microgrid operations. The selected candidate will develop and evaluate advanced algorithms for applications such as secure and adaptive control, anomaly and attack detection, resilient decision-making, and AI-enabled operational support for highly distributed grids. The postdoctoral appointee will work closely with multidisciplinary teams at Argonne and partner institutions and is expected to contribute to both methodological innovation and practical validation using simulation, co-simulation, or hardware-relevant environments.</p><p></p><p>Primary Responsibilities:</p><ul><li><p>Develop machine learning and AI methods for control, optimization, and cyber-resilient operation of distribution systems, DER, and networked microgrids.</p></li><li><p>Design and implement reinforcement learning, game-theoretic, or robust decision-making approaches for adaptive control of DER and microgrids under uncertainty and adversarial conditions.</p></li><li><p>Develop methods for cyberattack detection, anomaly identification, intrusion-aware control, and resilient system recovery in cyber-physical energy systems, including DER-rich distribution networks.</p></li><li><p>Integrate domain knowledge from power systems with modern ML methods to create physics-informed, interpretable, and operationally relevant solutions.</p></li><li><p>Build and evaluate models using realistic utility or test-system data, simulation platforms, and digital-twin or real-time environments as appropriate.</p></li><li><p>Collaborate with researchers across power systems, controls, cybersecurity, and AI/ML to develop publications, technical reports, software tools, and project deliverables.</p></li><li><p>Present research results at technical meetings, workshops, and leading conferences, and publish in high-impact journals.</p></li></ul><p></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Position Requirements</b></p><ul><li><p>Recent or soon-to-be completed (typically within the last 0-5 years ) Ph.D. in Computer Science, Electrical Engineering, or a related field.</p></li><li><p>Demonstrated research expertise in AI and machine learning, with application to power systems, control, optimization, or cybersecurity.</p></li><li><p>Programming skills in Python and experience with at least one modern machine learning framework such as PyTorch or TensorFlow.</p></li><li><p>Demonstrated experience in at least one of the following: reinforcement learning, control or optimization for cyber-physical systems, anomaly detection, cybersecurity for operational systems, or decision-making under uncertainty.</p></li><li><p>Working knowledge of electric power systems, with emphasis on distribution systems, microgrids, or inverter-based resources.</p></li><li><p>Evidence of scholarly research productivity, such as peer-reviewed journal papers, conference publications, technical reports, or an equivalent research record.</p></li><li><p>Skilledritten and verbal communication skills and the ability to work effectively in a multidisciplinary research environment.</p></li><li><p>Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.</p></li><li><p>This position requires an on-site presence at the Argonne campus in Lemont, Illinois.</p></li></ul><p></p><p>Preferred Qualifications:</p><ul><li><p>Direct research experience at the intersection of machine learning and power system operation, especially for distribution systems, and microgrids.</p></li><li><p>Experience with power system simulation or analysis tools such as OpenDSS or similar platforms.</p></li><li><p>Experience with real-time simulation, co-simulation, digital twins, hardware-in-the-loop, or testbed-based validation.</p></li><li><p>Experience working with utility, field, or experimentally derived datasets relevant to grid operations, control, or cybersecurity.</p></li><li><p>Experience contributing to collaborative research software, reproducible workflows, or open-source tool development.</p></li></ul><p></p><p>Application Procedure:<br />Interested candidates should submit:</p><ul><li><p>A detailed CV</p></li><li><p>A cover letter describing your research experience and interests.</p></li><li><p>GitHub profile (if available)</p></li></ul><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Family</b></p>Postdoctoral<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Job Profile</b></p>Postdoctoral Appointee<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Worker Type</b></p>Long-Term (Fixed Term)<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><b>Time Type</b></p>Full time<p style="text-align:inherit"></p><p style="text-align:inherit"></p><h3></h3>The expected hiring range for this position is $72,879.00-$121,465.00.<h3></h3><p style="text-align:inherit"></p><p style="text-align:left"><span><span>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. </span></span></p><p style="text-align:inherit"></p><p style="text-align:left">Click <a target="_blank" href="https://www.anl.gov/hr/healthcare-insurance"><span><u>here</u></span></a> to view Argonne employee benefits!</p><h3></h3><p style="text-align:inherit"></p><p><i><span>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.</span></i></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p style="text-align:left"><i>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&#39;s Legal Department.  </i></p><p style="text-align:inherit"></p><p style="text-align:left"><i>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.</i></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Postdoctoral Appointee – Machine Learning, Control, and Cybersecurity for Power Systems

PhD in Computer Science or Electrical/Power Engineering; AI/ML for power systems; Python with PyTorch/TensorFlow; RL/control/optimization experience; knowledge of distribution systems and microgrids; strong communication; on-site at Lemont, IL.

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