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analysis Integration of molecular profiles with circuit data Development of reproducible pipelines for large-scale datasets CRISPR-based functional genomics This is a full-time position available from
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
Posting Information Posting Details Department Physics and Astronomy - 319000 Posting Open Date 11/24/2025 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar Position
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and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have recently completed (or be close to completing) a PhD in
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Service) applications support the C3S Agriculture Micro-site and Mediterranean Demonstrator with agronomic insights and data Your qualifications: PhD in crop science, computational environmental science, or
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28 Nov 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Modelling tools Computer science » Programming Engineering » Civil
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Institute of Metabolic and Cardiovascular Diseases (Toulouse) | Toulouse, Midi Pyrenees | France | 6 days ago
24 Nov 2025 Job Information Organisation/Company Institute of Metabolic and Cardiovascular Diseases (Toulouse) Research Field Biological sciences » Biology Researcher Profile Recognised Researcher
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LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Extended knowledge of magnetised plasma physics (PhD), ideally in the context of tokamak plasmas
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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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to evaluate disequilibrium in trait–environment relationships across time and space. Analyze trait, fossil, and environmental datasets to assess climate tracking and climate fidelity. Collaborate with a large
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 13 hours ago
supermassive black holes through a combination of observational data, machine learning techniques, and cosmological simulations. The group is actively involved in multiple JWST Guaranteed Time Observation (GTO