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Field
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. Responsibilities and qualifications Qualifications: PhD degree in Engineering, Physics, Computer Science, or Applied Mathematics. Proficiency in scientific programming with Python. Excellent oral and written
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. Programming or scripting skills (e.g., Python, R, or MATLAB) for exposure modeling or database automation. Other Competencies Ability to work in interdisciplinary, international teams. Strong communication and
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areas: Knowledge of computer science and operations research Familiarity with renewable energy systems and their challenges Proficiency in programming languages such as Python or Julia Strong problem
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or optimization. Proven experience with programming and data analysis tools. Fluency in Python, including experience writing data analysis scripts and model training code. Experience with scientific computing and
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multidisciplinary team environment. Further, we will prefer candidates with some of the following qualifications: Solid background in programming using Python (PyTorch, TensorFlow), R or other languages. Experience
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multidisciplinary team environment. Further, we will prefer candidates with some of the following qualifications: Solid background in programming using Python (PyTorch, TensorFlow), R or other languages. Experience
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equivalent to a two-year master's degree. Additional qualifications include: Good programming skills in Python, Julia, R or similar, and familiarity with C, C# or C++. Curiosity and interest in future urban
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, electrical engineering, communication engineering, computer science, or a related field. Documented experience with deep learning techniques (e.g., CNNs, Transformers) Strong programming skills in Python and
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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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(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