Qureos Mentor

Argonne National Laboratory

<div><div>The Advanced Photon Source (APS) (<div>https://www.aps.anl.gov/</div>) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to build a physics-informed AI framework that decodes the complex relationships between material defects, functional fields (e.g., strain, electrostatic potential), and device performance, with a primary focus on leveraging advanced synchrotron X-ray techniques.</div><div></div><div>
The successful candidate will be at the forefront of integrating cutting-edge AI methodologies with world-leading X-ray characterization. You will develop and apply novel machine learning models&mdash;including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning&mdash;to fuse multimodal data from diverse experimental probes like Bragg Coherent Diffraction Imaging (BCDI), ptychography, and X-ray Photon Correlation Spectroscopy (XPCS). The goal is to move beyond simple correlations to discover the causal, governing rules of defect-property relationships in next-generation electronic materials.</div><div></div><div>
This role involves creating AI models for real-time data analysis, enabling autonomous experiments through active learning and &quot;curiosity-driven&quot; exploration, and contributing to a robust data infrastructure that makes large-scale, multimodal datasets FAIR and AI-ready. You will publish findings in high-impact journals, present at major international conferences, and work within a large, interdisciplinary team of experts from multiple national laboratories and universities.</div><div></div><div>
The appointee will benefit from direct access to the unique capabilities of the upgraded APS, leadership-class computing at the Argonne Leadership Computing Facility (ALCF), and state-of-the-art microscopy at the Center for Nanoscale Materials (CNM). Candidates with a strong background in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply.</div><div></div><div>
Position Requirements</div><ul><li><div>
PhD completed in the past 5 years or soon to be completed in a relevant field of study.</div></li><li><div>
Experience with deep learning (DL) frameworks such as PyTorch, TensorFlow, or JAX.</div></li><li><div>
Strong programming proficiency in Python.</div></li><li><div>
Demonstrated experience with coherent X-ray techniques (e.g., BCDI, ptychography, XPCS) and associated data analysis.</div></li><li><div>
Ability to model Argonne&rsquo;s core values of impact, safety, respect, integrity, and teamwork.</div></li><li><div>
Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.</div></li></ul><div></div><div>
Preferred Knowledge, Skills, and Experience:</div><ul><li><div>
Experience with scientific AI techniques like Physics-Informed Neural Networks (PINNs) and geometric deep learning.</div></li><li><div>
Experience with active learning, agentic workflows, or other methods for autonomous experimentation.</div></li><li><div>
Familiarity with high-performance computing (HPC) environments and large-scale data management.</div></li><li><div>
Experience with version control (e.g., Git) and collaborative software development practices.</div></li><li><div>
Experience with real-time analysis and instrument control at a user facility.</div></li><li><div>
Skill in both written and oral scientific communication.</div></li><li><div>
A strong track record of working collaboratively in a diverse, team-oriented research environment.</div></li></ul><div></div><div>
Job Family</div>
Postdoctoral<div></div><div>
Job Profile</div>
Postdoctoral Appointee<div></div><div>
Worker Type</div>
Long-Term (Fixed Term)<div></div><div>
Time Type</div>
Full time<div></div>
The expected hiring range for this position is $70,758.00-$117,925.00.<div></div><div>
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.</div><div></div><div>
Click <div>here</div> to view Argonne employee benefits!</div><div></div><div><i>
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.</i></div><div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><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's Legal Department.</i></div><div></div><div><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></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></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 for Coherent X-ray Imaging

<div></div><div><div>The High Energy Physics Division at Argonne National Laboratory invites applications for a postdoctoral research associate position to conduct research in machine learning (ML) for applications in High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple HEP experiments. Experiments with Argonne involvement include, but are not limited to, ATLAS at CERN, the South Pole Telescope, and the Simons Observatory.</div><div></div><div>
The candidate is also expected to work closely with computational experts at the Computational Science (CPS) division, designing and executing ML experiments on leadership-class computing facilities such as the Aurora and Polaris supercomputers. Argonne is a multidisciplinary national laboratory and offers an exciting campus atmosphere in which to collaborate on interdisciplinary projects, at both the national and international levels. The initial appointment will be for one year, with possibility of renewal for another two years and is based at Argonne National Laboratory (Lemont, Illinois).</div><div></div><div>
Position Requirements</div><div></div><ul><li><div>
Recent or soon-to-be-completed PhD (within the last 0-5 years) in high energy physics, or a related field</div></li><li><div>
Experience with applying unsupervised ML algorithms such as autoencoders, clustering, to time-series data is preferred</div></li><li><div>
Experience with the data from HEP experiments is strongly required</div></li><li><div>
Programming expertise in Python and either PyTorch or TensorFlow is required</div></li><li><div>
Experience using High-Performance Computers (HPCs) is preferred</div></li><li><div>
Ability to model Argonne&rsquo;s Core Values: Impact, Safety, Respect, Integrity, and Teamwork</div></li></ul><div></div><div>
Openings are available immediately; there is flexibility in starting dates for highly qualified candidates. Review of applications will begin immediately and applications that are received by December 1, 2025, will receive priority. The positions will remain open until filled.</div><div></div><div>
Complete applications must include:</div><ul><li><div>
Curriculum vitae</div></li><li><div>
A description of research interests</div></li><li><div>
Arrange for three letters of recommendation to <div>HEPHR@anl.gov</div></div></li></ul><div></div><div>
For further information and questions please contact Walter Hopkins at whopkins@anl.gov.</div><div></div><div>
Job Family</div>
Postdoctoral<div></div><div>
Job Profile</div>
Postdoctoral Appointee<div></div><div>
Worker Type</div>
Long-Term (Fixed Term)<div></div><div>
Time Type</div>
Full time<div></div>
The expected hiring range for this position is $70,758.00-$117,925.00.<div></div><div>
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.</div><div></div><div>
Click <div>here</div> to view Argonne employee benefits!</div><div></div><div><i>
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.</i></div><div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><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's Legal Department.</i></div><div></div><div><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></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></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 Research Associate - Machine Learning in High Energy Physics Detector Operations

<div><div><i>Argonne National Laboratory is a Department of Energy national laboratory with over 1,500 scientists and engineers performing world-class research aimed at solving the nation's energy, environmental and security challenges. Argonne is located 25 miles southwest of Chicago on a beautiful 1,500-acre campus.</i></div><div></div><div><br>
The Decision and Infrastructure Sciences (DIS) division researches, designs, and delivers scientific tools and methodologies to inform decision-making regarding the most challenging security, risk, and resilience problems. As a multidisciplinary national laboratory, Argonne offers an exciting atmosphere in which to collaborate on interdisciplinary projects that focus on complex technical problems and integrated application of natural, social, and computer science practices.</div><div></div><div>
To assist our research mission, DIS is seeking a Computational Scientist to strengthen current and future applications of artificial intelligence (AI), machine learning (ML), agent-based modeling, and related modeling and simulation capabilities across the Division&rsquo;s research portfolio, including topics related to infrastructure security and resilience, energy security, economic security, and emergency management. Successful candidates should be familiar with performing advanced data analysis across different technical domains; developing predictive models, simulations, and optimization algorithms; and collaborating with multi-disciplinary teams to identify and address key operational challenges.</div><div></div><div>
This role includes statistical analysis using a variety of modeling techniques, developing prototype solutions using scientific programming languages, designing experiments for validation and testing efficacy of models, and measuring impact. The role involves identifying concepts and developing procedures for investigating problems of a significant nature, which may be broadly stated or ill-defined.</div><div></div><div><br>
In this position, you will:</div><ul><li><div>
Contribute to projects associated with AI/ML, high-performance computing (HPC), and computational problems related to the Division&rsquo;s core missions and sponsors.</div></li><li><div>
Develop novel methodologies and contribute to emerging technical approaches that apply AI/ML and agent-based modeling to sponsored research that informs decision-making across a broad range of industry and community stakeholders.</div></li><li><div>
Work with an interdisciplinary team of domain scientists (e.g., decision science, computational scientists, engineers, infrastructure analysts, etc.) to develop decision-ready toolsets based upon AI/ML approaches.</div></li><li><div>
Contribute to projects associated with Large Language Model (LLM) toolset development for decision science applications among industry and community stakeholders.</div></li><li><div>
Support engagements with DOE and other federal entities, State, Local, Tribal, and Territorial governments, and industry sponsors to inform the development of AI/ML tools that best align with stakeholder decision needs.</div></li><li><div>
Interface with subject matter experts in key fields from across Argonne to produce decision-relevant AI/ML resources across a range of scientific domains in the DIS sponsored research portfolio.</div></li><li><div>
Work with DIS and other Argonne subject matter experts to support government sponsors interested in a wide range of both domestic and international AI/ML-informed decision-support.</div></li></ul><div></div><div>
Open to the following work locations:</div><ul><li><div>
Hybrid work schedules for individuals in the Chicago, IL region, or</div></li><li><div>
Remote with travel expectations between 10-15% dependent on sponsor needs.</div></li></ul><div></div><div>
Position Requirements</div><ul><li><div>
Minimum Education/Experience Requirement: Bachelor's and 0+ years, Master's and 0+ years or equivalent</div></li><li><div>
Experience performing AI/ML-related activities, including data identification, cleansing and preparation, algorithm development, statistical learning, and validation of results.</div></li><li><div>
Experience working with generative AI, natural language processing, network modeling, and AI assistant models is preferred.</div></li><li><div>
Knowledge and experience with coding languages including Python, MatLab, SQL, Java, and Julia.</div></li><li><div>
Knowledge and experience with machine learning libraries including TensorFlow, PyTorch, Scikit-learn, Pandas, and Numpy.</div></li><li><div>
Knowledge and experience with modeling and simulation, including agent-based modeling, Monte Carlo, and life cycle assessment.</div></li><li><div>
Ability to use independent judgment and abstract from specific problems to general solutions/findings.</div></li><li><div>
Strong oral and written communications skills, including the ability to translate technical information into plain language, and strong ability to work effectively in a team-based project environment.</div></li><li><div>
Skill and experience working on multiple projects simultaneously, including sound project management practices and the ability to manage deadlines effectively.</div></li><li><div>
Skill and experience collaborating with team members and leading independent analysis in support of projects.</div></li><li><div>
A successful candidate must have the ability to model Argonne&rsquo;s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.</div></li></ul><div></div><div>
Other:</div><div>
Selected candidate will be required to obtain and maintain a clearance and must be a U.S. citizen. Please see <div>http://www.state.gov/m/ds/clearances/c10978.htm</div> for more information about requirements for obtaining a security clearance process.</div><div></div><div>
Job Family</div>
Research Development (RD)<div></div><div>
Job Profile</div>
Computational Science 1<div></div><div>
Worker Type</div>
Regular<div></div><div>
Time Type</div>
Full time<div></div>
The expected hiring range for this position is $74,799.00 - $118,785.42.<div></div><div>
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.</div><div></div><div>
Click <div>here</div> to view Argonne employee benefits!</div><div></div><div><i>
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.</i></div><div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><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's Legal Department.</i></div><div></div><div><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></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Assistant Computational Data Scientist

Join Argonne National Laboratory and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Argonne National Laboratory

ABOUT_COMPANY

Postdoctoral Appointee - AI for Coherent X-ray Imaging

Postdoctoral Research Associate - Machine Learning in High Energy Physics Detector Operations

Assistant Computational Data Scientist