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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 2 months ago
chemistry methods applicable to biomolecular systems, which are then applied to computer-aided drug design. We are looking for a talented postdoctoral fellow to join our team and work on the development
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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areas : 1/ Development of methods to estimate residential environmental exposures • Develop spatialized indicators of exposure to atmospheric contaminants (gaseous pollutants and pesticides) based
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The University of Lincoln is seeking a highly motivated Research Associate with expertise in robotic perception and computer vision to join our internationally recognised Agri-Robotics research team
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 18 days ago
Carolina, US Hiring Range $63,480 - $77,076 Proposed Start Date Estimated Duration of Appointment 24 Months Position Information Be a Tar Heel! A global higher education leader in innovative teaching
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computational methods and collaboration, HELM addresses global challenges by blending eco-social health determinants, human-natural system interactions, and convergence research. The selected candidate will work
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methods development and good analytical practices Maintains a working knowledge of significant developments and trends in the field SKILLS Outstanding proposal and paper writing skills Excellent
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advances the development and application of AI methods for quantum computing, as well as the use of quantum-inspired approaches to enhance AI systems. Artificial intelligence and quantum computing
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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, optimization, and characterization integrating imaging, experimental metadata, and diffraction outcomes. Design and deploy computer vision methods to detect and track crystal growth. Develop closed-loop