<p>Argonne Vehicle and Mobility Systems department (VMS) at Argonne National Laboratory is seeking a Predoctoral Appointee to support research and development efforts through data engineering, machine learning and applied software development. The position focuses on transforming complex, large-scale datasets into actionable insights and deployable analytical capabilities that support research, modeling, and decision-making. The Predoctoral Appointee will participate in the design, development, and evaluation of data-driven systems and analytical workflows that support large-scale data modeling and analytics. The role requires a strong foundation in data science and data engineering, with the ability to build efficient, reusable, and scalable data workflows from data collection, data integration, and data management through analysis, machine learning model development, deployment, and visualization.</p><p></p><p>The Predoctoral Appointee will collaborate closely with multidisciplinary research teams to support research and analytical data needs.</p><p>Job Responsibilities:</p><ul><li><p>Designing and implementing end-to-end ETL and data processing pipelines to collect, ingest, clean, transform, store, and query large-scale datasets from diverse sources.</p></li><li><p>Developing and maintaining data engineering workflows using Python.</p></li><li><p>Building, training, tuning, and evaluating machine learning models for regression, classification, clustering, and anomaly detection tasks.</p></li><li><p>Integrating structured, semi-structured, and unstructured data into unified analytical datasets.</p></li><li><p>Collaborating with researchers to deploy data products.</p></li><li><p>Creating visualizations, dashboards, or analytical reports to communicate insights and model results to technical and non-technical stakeholders.</p></li><li><p>Supporting data quality assessment, exploratory data analysis, and model interpretability efforts.</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 Master’s degree in Computer Science, Data Science, Data Analytics, Software Engineering, Data Engineering, Machine Learning, Applied Statistics.</p></li><li><p>Background in data science, computer science, engineering, statistics, applied mathematics, or a related field.</p></li><li><p>Demonstrated experience applying data science and machine learning techniques to real-world or research-driven problems.</p></li><li><p>Analytical and problem-solving skills, with the ability to translate research questions into data-driven solutions.</p></li><li><p>Ability to work collaboratively in a research environment and communicate technical concepts effectively.</p></li><li><p>Proficiency in Python for data analysis, data engineering, and machine learning.</p></li><li><p>Experience developing and maintaining data pipelines using workflow orchestration or scheduling tools.</p></li><li><p>SQL skills and experience working with relational databases, familiarity with NoSQL or document-based databases.</p></li><li><p>Experience with large-scale data processing frameworks.</p></li><li><p>Experience integrating data from multiple and heterogeneous sources.</p></li><li><p>Experience applying machine learning techniques, including supervised and unsupervised learning, model evaluation, and hyperparameter tuning.</p></li><li><p>Experience with software development best practices, including version control, testing, documentation, and code review.</p></li><li><p>Experience with data visualization tools or libraries.</p></li><li><p>A successful candidate must have the ability to model Argonne’s Core Values: 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 style="text-align:inherit;"></p><p style="text-align:inherit;"></p><p style="text-align:left;"><b>Job Family</b></p>Temporary<p style="text-align:inherit;"></p><p style="text-align:inherit;"></p><p style="text-align:left;"><b>Job Profile</b></p>Predoctoral 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 $58,297.00-$97,161.00.<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 href="https://www.anl.gov/hr/healthcare-insurance"><span>here</span></a> to view Argonne employee benefits!</p><h3></h3><p style="text-align:inherit;"></p><p><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></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;">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.  </p><p style="text-align:inherit;"></p><p style="text-align:left;">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.</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 class="break-words white-space-pre-wrap t-black--light text-body-medium">Argonne National Laboratory, one of the U.S. Department of Energy's national laboratories for science and engineering research, employs 3,400 employees, including 1,400 scientists and engineers, three-quarters of whom hold doctoral degrees. Argonne's annual operating budget of around $1 billion supports upwards of 200 research projects. Since 1990, Argonne has worked with more than 600 companies and numerous federal agencies and other organizations. Argonne's mission is to apply a unique mix of world-class science, engineering and user facilities to deliver innovative research and technologies. We create new knowledge that addresses the most important scientific and societal needs of our nation. We actively seek opportunities to work with industry to transfer our technologies to the marketplace through licensing, joint research and many other collaborative relationships. Argonne is managed by UChicago Argonne, LLC, for the U.S. Department of Energy's Office of Science. We are located on 1,500 acres (6.9 sq. km) in southwest DuPage County, Illinois 25 miles (40 km) southwest of Chicago. The site is completely encircled by the beautiful Waterfall Glen Forest Preserve.</p>

Predoctoral Appointee - Engineer Research Associate

<p>Argonne Vehicle and Mobility Systems department (VMS) at Argonne National Laboratory is seeking a Predoctoral Appointee to support research and development efforts through data engineering, machine learning and applied software development. The position focuses on transforming complex, large-scale datasets into actionable insights and deployable analytical capabilities that support research, modeling, and decision-making. The Predoctoral Appointee will participate in the design, development, and evaluation of data-driven systems and analytical workflows that support large-scale data modeling and analytics. The role requires a strong foundation in data science and data engineering, with the ability to build efficient, reusable, and scalable data workflows from data collection, data integration, and data management through analysis, machine learning model development, deployment, and visualization.</p><p></p><p>The Predoctoral Appointee will collaborate closely with multidisciplinary research teams to support research and analytical data needs.</p><p>Job Responsibilities:</p><ul><li><p>Designing and implementing end-to-end ETL and data processing pipelines to collect, ingest, clean, transform, store, and query large-scale datasets from diverse sources.</p></li><li><p>Developing and maintaining data engineering workflows using Python.</p></li><li><p>Building, training, tuning, and evaluating machine learning models for regression, classification, clustering, and anomaly detection tasks.</p></li><li><p>Integrating structured, semi-structured, and unstructured data into unified analytical datasets.</p></li><li><p>Collaborating with researchers to deploy data products.</p></li><li><p>Creating visualizations, dashboards, or analytical reports to communicate insights and model results to technical and non-technical stakeholders.</p></li><li><p>Supporting data quality assessment, exploratory data analysis, and model interpretability efforts.</p></li></ul><p></p><p></p><p></p><p><b>Position Requirements</b></p><ul><li><p>Recent or soon-to-be completed Master’s degree in Computer Science, Data Science, Data Analytics, Software Engineering, Data Engineering, Machine Learning, Applied Statistics.</p></li><li><p>Background in data science, computer science, engineering, statistics, applied mathematics, or a related field.</p></li><li><p>Demonstrated experience applying data science and machine learning techniques to real-world or research-driven problems.</p></li><li><p>Analytical and problem-solving skills, with the ability to translate research questions into data-driven solutions.</p></li><li><p>Ability to work collaboratively in a research environment and communicate technical concepts effectively.</p></li><li><p>Proficiency in Python for data analysis, data engineering, and machine learning.</p></li><li><p>Experience developing and maintaining data pipelines using workflow orchestration or scheduling tools.</p></li><li><p>SQL skills and experience working with relational databases, familiarity with NoSQL or document-based databases.</p></li><li><p>Experience with large-scale data processing frameworks.</p></li><li><p>Experience integrating data from multiple and heterogeneous sources.</p></li><li><p>Experience applying machine learning techniques, including supervised and unsupervised learning, model evaluation, and hyperparameter tuning.</p></li><li><p>Experience with software development best practices, including version control, testing, documentation, and code review.</p></li><li><p>Experience with data visualization tools or libraries.</p></li><li><p>A successful candidate must have the ability to model Argonne’s Core Values: 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></p><p><b>Job Family</b></p>Temporary<p></p><p></p><p><b>Job Profile</b></p>Predoctoral Appointee<p></p><p></p><p><b>Worker Type</b></p>Long-Term (Fixed Term)<p></p><p></p><p><b>Time Type</b></p>Full time<p></p><p></p><h3></h3>The expected hiring range for this position is $58,297.00-$97,161.00.<h3></h3><p></p><p><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></p><p>Click <a href="https://www.anl.gov/hr/healthcare-insurance"><span>here</span></a> to view Argonne employee benefits!</p><h3></h3><p></p><p><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></p><p></p><p></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>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. &nbsp;</p><p></p><p>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. &nbsp;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. &nbsp;Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.</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>

Predoctoral Appointee - Engineer Research Associate

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Argonne National Laboratory

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