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Field
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modeling is advantageous Good programming skills (e.g., Python) High degree of independence and willingness to show great commitment Very reliable and conscientious work style Fluent written and spoken
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, ideally in Python, with demonstrated experience in applying them in complex research or development projects Basic knowledge in Machine Learning, ideally supported by initial hands-on experience Experience
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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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related field of study • Interest in energy technology and energy economics • Experience in energy system modelling is an advantage • Basic programming skills, ideally in Python • Independent and analytical
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Familiarity with statistics and programming experience in Python are advantageous Strong intention to be a part of international team with interdisciplinary questions We offer: An interesting and vibrant field
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qualifications: a MSc degree in oceanography, fluid mechanics, geosciences, physics, mechanical engineering or related disciplines programming skills in one or more languages (Matlab, Python, R, C, Fortran
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use other programmes, such as Python, Stata, or SAS. Application deadline Please check the HDS PhD website in autumn 2025 for updated information on 2026 HDS PhD programme admissions. The application
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, sociological...) to measuring beliefs, attitudes, and their relationship with shaping (online) behavior is desirable. Familiarity with data analysis in R or Python is required. Experience in study handling
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soil characterization techniques. A strong command of English is indispensable. Skills in R, MATLAB or Python are helpful. The effective exchange within the interdisciplinary collaboration will be
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, chemistry, material science, chemical engineering or related disciplines Experience in the field of energy storage Knowledge of X-ray methods Experience with programming languages (ideally Python) Fluent in