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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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responsibilities simultaneously. 3.Proficiency in Microsoft Office Suite, including Word, Excel, and Outlook, with the ability and willingness to learn new databases and computer applications. 4.Professionalism
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 12 days ago
shape the next generation of agentic AI tools for biomedical research. A highly interdisciplinary environment connecting AI, computational biology, human–computer interaction, and research software
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of the researchers of the DKM group are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) . The candidate is expected to join Integreat and strengthen the interdisciplinary
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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for the hydrogen workforce. Project Focus This Postdoc Research Aims To: Examine how remote labs and digital learning environments can accelerate skill development and reduce time-to-job for hydrogen professionals
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expertise in machine learning or computational modelling who are eager to advance conceptual innovation toward practical industrial deployment. Qualifications PhD in Computer Science, Machine Learning