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proficiency in coding, at least using Bash and Python. Applicants should maintain their code in a public repository (e.g. GitHub) and include the link in their application. Proven skills in Linux/HPC
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modeling, molecular interactions/energetics, and tools such as AlphaFold, Rosetta, or MD simulations. Solid programming skills (Python); familiarity with machine learning is a plus. For both profiles, we
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statistical software such as R, Python, SPSS, or Stata. Affinity with issues of climate justice, social inclusion, migration, and/or community-based research. Experience conducting comparative or mixed-methods
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methods for audio data. A publication record in ML applied to bioacoustics is a bonus; Good programming skills in Python. Familiarity with ML frameworks (PyTorch, Tensorfiow, Jax) is a bonus; Demonstrated
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to damage or loss data; Experience with programming (Python or R) and working with large datasets; Ability to design and evaluate field experiments or quasi‑experimental studies is an asset; Strong written
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with user studies, preferably qualitative methods such as interviews, think-alouds or focus groups; significant coding experience in Python; experience with LLMs, in particular as part of agentic systems
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tracking, pupillometry or related psychophysiological methods, or is eager to acquire these techniques; has strong quantitative and statistical skills (preferably using R and/or Python); demonstrates
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, or a related field; Good publication record in ML, and/or computational methods for audio data. A publication record in ML applied to bioacoustics is a bonus; Good programming skills in Python
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science or remote sensing, or a related field. Good programming skills (e.g., Python). Familiarity with satellite data or other large numeric data files. Knowledge of physics or biophysics. Knowledge
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analytical and problem-solving skills. Experience with data analysis, numerical modelling or programming, for example in MATLAB, Python or similar tools. Good written and verbal communication skills in English