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, mathematics or related majors Job Description: The Postdoctoral Researcher will play a key role in developing and applying cutting-edge AI methods to analyze large-scale clinical datasets, including electronic
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 4 days ago
research team. The ideal candidate should have: A PhD/DPhil degree (or comparable) with a background in theoretical physics, applied mathematics or related disciplines from a recognized university; Prior
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terminal degree in Civil or Environmental Engineering, hydrology, ecology, geosciences, computer science, applied mathematics, data analytics, or related fields at the start date. Candidates will need
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Brown University, Division of Applied Mathematics Position ID: BrownAPMA -PAP [#26844] Position Title: Position Type: Non tenure-track faculty Position Location: Providence, Rhode Island 02906
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, applied mathematics. - A strong background in theoretical mechanics and applied mathematics, with an expertise in artificial intelligence. Expertise in design, social sciences or humanities are a plus; - A
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the NIH Center to iteratively refine learned models. Qualifications: • Ph.D. in applied mathematics, computational science, statistics, machine learning, or related quantitative field. • Proficiency with
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Université de Technologie de Belfort-Montbéliard | Belfort, Franche Comte | France | about 6 hours ago
22 Aug 2025 Job Information Organisation/Company Université de Technologie de Belfort-Montbéliard Department Mechanical engineering Research Field Engineering » Mechanical engineering Mathematics
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, and easy to extend and develop. REQUIRED: Ph.D., in applied mathematics, atmospheric or oceanic sciences, computer science, engineering, physics, statistics, or a related field by the date of hire
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Qualifications: Ph.D. or other terminal degree in terminal degree in Civil or Environmental Engineering, hydrology, ecology, geosciences, computer science, applied mathematics, data analytics, or related fields
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to massive datasets, scientists today rely on advances in and integration across applied mathematics, computer science, and computational science, as well as large-scale computing and networking facilities