38 parallel-programming-"DIFFER"-"Mohammed-VI-Polytechnic-University" Fellowship positions at University of Bergen
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condition of employment that the master's degree has been awarded. Computer programming experience using languages such as for example Python or C++ is a requirement. It is an advantage with a master’s degree
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been employed in a qualifying post (e.g. research fellow, research assistant). About the research training As a PhD Research Fellow, you must participate in an approved educational programme for a PhD
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Fellow, you must participate in an approved educational programme for a PhD degree within a period of 3 years. The deadline for applying for admission to the PhD programme at The Faculty of Science and
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an approved educational programme for a PhD degree within a period of 3 years. The deadline for applying for admission to the PhD programme at The Faculty of Science and Technology is 2 months after you start
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to the research project itself. The remaining six months will be allocated to formal training. As a PhD candidate, you must participate in the Faculty of Humanities’ educational programme . The PhD programme
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will be allocated to formal training. As a PhD candidate, you must participate in the Faculty of Humanities’ educational programme . The PhD programme comprises a training component corresponding to 30
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must participate in an approved educational programme for a PhD degree within a period of 4 years. The deadline for applying for admission to the PhD programme at The Faculty of Science and Technology is
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programme: LEAD AI is the University of Bergen's career and mobility fellowship program for training 19 postdoctoral fellows in artificial intelligence. The program has received funding from the European
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previously been employed in a qualifying post (e.g. research fellow, research assistant). About the research training As a PhD Research Fellow, you must participate in an approved educational programme for a
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. The position is for a fixed term of 3 years and is associated with the LEAD AI project co-funded by European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant