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. Python/Julia/Matlab). Excellent written and oral English. The appointment is to be made in accordance with NTNUs guidelines for recruitment positions and the regulations for the Act relating
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into the innovative field of hydrogen technology; ideally complemented by knowledge in computer science for modeling and simulation (Python/MATLAB/Simulink), enabling you to efficiently analyze complex supply chains
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Strong analytical, research, and scientific writing skills Proficiency in Python for modeling and machine learning applications Effective communication, teamwork, and presentation abilities Self-motivated
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, presentations, and draft manuscripts. Proficiency in hard skills, such as implementing and evaluating algorithms in Python, and maintaining reproducible experimentation. Competent in soft skills, such as problem
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elements in nonlinear analysis software (preferred Atena); • Documented experience in other software for nonlinear analysis of structures; the ability to use a programming environment (e.g., Python) will
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Strong planning, organizational and analytical skills Excellent communication skills, both written and verbal Proficiency in programming languages (Python, R, or bash) Be familiar with single-cell RNA-seq
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Schools (or similar training activities) specialized in these fields of at least 30 hours: 10 points each. -- Same as above, lasting at least 15 hours: 5 points each. A.5. Demonstrable knowledge of Python
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-solving skills. Prior experience with prototyping or fabrication (for example, CAD, 3D printing, or machining) is desirable but not required. Familiarity with MATLAB and/or Python is preferred. Additional
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platforms including the MS suite of software, GitHub, R, and Python. Works under supervision and independently to perform basic (descriptive analyses), moderately advanced statistical analyses (inferential
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proficiency in Python, R, or MATLAB. Experience with Deep Learning frameworks (PyTorch, TensorFlow) and LLM APIs is an asset. Communication: Fluent English skills, both written and spoken, with a demonstrated