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information services Educational sciences » Learning studies Educational sciences » Research methodology Information science » Information management Information science » Library science Information
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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience
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to SAFE. Delivering EVU course from SAFE center. Required selection criteria A PhD degree (or equivalent) in biometrics, information security, computer science, electrical engineering, or machine learning
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with lab members on projects; (e) Writing manuscripts and presenting at conferences; and (f) Assisting with maintaining shared lab resources, such as IRB protocols. This is an excellent and unique
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willingness to learn new technologies, and the ability to translate research into high-quality outputs. Where to apply E-mail geogsekr@savba.sk Requirements Research FieldGeographyEducation LevelPhD
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Senior Researcher in Ecosystem based marine management, nature restoration, and anthropogenic imp...
to mutual agreement). The position is a part-time position for 10 hours/ per week. You can read more about career paths at DTU here . Further information Further information may be obtained from Grete E
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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
Toxicology and other departments and centers at the Brody School of Medicine and East Carolina University. The tenure-track faculty member will also be expected to teach pharmacology and/or toxicology
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Professor (25260446) Responsibilities: The Department is recruiting one scholar at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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the field of frugal or green AI TECHNICAL SPHERE You have a proven experience in frugal, green or low-resource AI Strong grasp of deep learning architectures (CNN, RNN, Transformers, LLMs). Experience in fine