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Postdoctoral Research Associate will be responsible for AI-driven materials discovery. The position will collaborate with interdisciplinary teams to develop integrated molecular simulation and machine learning
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simulations and experiments across scientific user facilities, leveraging data to understand complex material phenomena across scales. Key Responsibilities Design, implement, and validate physics-informed AI/ML
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. A copy of your PhD thesis Use the button at the foot of the page to reach the application form. A background check may be conducted as part of the application process. Please note: The applicant is
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The High Energy Physics Division at Argonne National Laboratory invites applications for a postdoctoral appointment focused on the design and simulation of advanced detectors for future high-energy
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour ago
, including transparency, blending, and perceptual separability. Develop and evaluate methods for perceptually grounded symbology selection, including simulation-based assessment across multiple background
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and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics calculations and Brownian Dynamics simulations. The group is looking
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, just apply via the "Apply now" button! Please enclose: your letter of motivation; your Curriculum vitae; minimum of 2 references (include name, phone number and email address); a copy of your PhD
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. Access to state‑of‑the‑art core facilities and an extensive network of national and international collaborators in vision science. Minimum Qualifications Preferences Ideal candidates will have a PhD or MD
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profile PhD in Health Economics, Development Economics, Public Health or similar disciplines (awarded or near completion) ; Demonstrated experience in CEA ; Experience with ECEA or DCEA analysis would be
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ongoing research activities within the School in a highly collaborative academic environment. The role will also involve training and supervising PhD students and junior research associates in