56 programming-"LIST"-"Humboldt-Stiftung-Foundation"-"U"-"U.S" positions at University of Southern Denmark
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institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme. List of publications and maximum 2 examples of relevant
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project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme. List of publications and
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or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme. List of publications
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complete and numbered list of publications 10 scientific peer-reviewed publications considered by the candidate as most important for this position. Please note that a copy of each publication must be
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or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme. List of publications
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possible. It is strictly required that you have experience with: Scientific programming, preferably in python and/or MATLAB and/or C++ Derivation and implementation of finite element methods (FEM) in code
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@iti.sdu.dk Conditions of employment The appointment as Associate Professor is permanent, while that as Assistant Professor is for an initial period of 4 years, part of a tenure-track programme. During
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related to research and/or teaching within some field of expertise including Data Science and fulfil many of the below listed requirements: Essential experience and skills MSc (or BSc plus minimum of 2
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related field. Strong software development and programming skills, with experience in designing and implementing complex software systems. Research experience in artificial intelligence and/or machine
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(deep neural networks) Probability theory Computer vision Robotics Programming skills (Python, C++) and ML libraries (PyTorch, Tensorflow) Preferably, the candidate has experience with: Bayesian machine