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problems and wave propagation from nano to kilometre scales. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer
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or Biomedical sciences (preferably with insight in sustainability aspects of nutrition) with specialization or additional training in data science or strong background in Data Science, computer science with a
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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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Computer science » Programming Technology » Biotechnology Researcher Profile Recognised Researcher (R2) Country Netherlands Application Deadline 29 Sep 2025 - 22:00 (UTC) Type of Contract Temporary Job
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assessment. You will be provided with access to various engineering and computation toolsets along with the high-performance computer. A good background in numerical methods and computational platforms is
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Port-city areas have stated ambitious goals
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This position is a good fit for you if you recognise yourself in the following: You hold a PhD in one these fields: computer science, information science, industrial ecology, operational research, environmental
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This position is a good fit for you if you recognise yourself in the following: You hold a PhD in one these fields: computer science, information science, industrial ecology, operational research, environmental
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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