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August 2025 Apply now Machine Learning models are increasingly important in the atmospheric sciences. After training, they can emulate model outcomes at a fraction of the computational cost of traditional
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. Qualifications We are looking for a candidate with A PhD in Computer Science, Operations Research, Applied Mathematics, Mathematics, Engineering, or a related discipline. Strong programming experience, for example
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are looking for candidates with: A PhD in Operations Research, Applied Mathematics, Mathematics, Engineering, or a related field. A background in logistics (preferred). Strong writing and presentation skills in
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: A PhD in Computer Science, Engineering, Mathematics, theoretical Physics or other degree programs from top universities involving at least one of the following topics: Machine Learning, AI, Dynamic
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: A PhD in Computer Science, Engineering, Mathematics, theoretical Physics or other degree programs from top universities involving at least one of the following topics: Machine Learning, AI, Dynamic
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, Linguistics and Media and Journalism Studies. For this role, we are looking for someone who: Has a PhD degree in any area related to the tasks (e.g. Computer Science, Digital Humanities, or Information Science
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. Your qualities For this interdisciplinary project, we are looking for a highly motivated and skilled postdoctoral researcher with a recent university PhD degree (or equivalent) in engineering, biology
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accommodate the development of your own line of research. Organization The Faculty of Spatial Sciences is a mid-sized faculty with approximately 100 members of staff, 100 PhD researchers and around 1000
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management related tasks will also be part of the candidate's responsibilities. Requirements Candidates are required to have a PhD degree in computer science, mathematics, electrical and electronic engineering
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for this position, the following is required: PhD in systems engineering, computer science or informatics, and the subject of the thesis should be relevant to the task description provided above (e.g. digital twin