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Field
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representation and knowledge graphs; programming skills in Python and knowledge of relevant NLP libraries (e.g. spaCy, Hugging Face Transformers); good English communication skills and an interest in
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techniques is an advantage • Prior experience with Python and R programming is considered an asset • Highly motivated, team-oriented, and well-organized • Good English communication skills (spoken and
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behavioral datasets Proficiency in scientific programming (e.g. Python, MATLAB, or R) for data analysis and visualization A clear affinity for insect behavior, sensory ecology, or movement ecology; Fieldwork
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Biology, Neuroscience/(neuro-)immunology, or related fields; preferably experience with big data and omics analyses and coding (e.g. python, R); affinity and experience with performing animal experiments
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Matlab, Python and C/C++ are preferred. Strong interpersonal skills and the capacity to work and learn independently will be required. English Language IELTS 6.0 Overall (with no individual component below
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Mathematical, Probabilistic and Engineering principles and methods. Familiarity with offshore engineering and wave-wind theories is advantageous. Experience in coding (e.g., Python) and in the use of Structural
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. Experience with these methods is a plus. Is skilled in programming and data analysis (e.g., Matlab, Python, R) Speaks and writes English fluently (Dutch is a plus) Works well in a team but is also self
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. Experience in coding (e.g., Python) and in the use of Structural Analysis Software (e.g., OpenSees, Abaqus) is highly desirable. Ability to work independently and take initiative in planning and executing
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/ Computer Science Electricity Markets or Power Systems in addition to solid programming skills (namely Python, Julia) and excellent command of the English language. We welcome candidates with varied experiences and
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programming experience (preferably in Python). If English is not your first language, provide evidence of proficiency through: A minimum IELTS average score of 6.5 and a minimum of 6.0 in each component. OR A