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programming languages (e.g., R, Python). Successful applicants should be self-motivated, well-organized, and able to work independently and collaboratively. Excellent written and oral communication skills
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with experience in One Health or climate-health research. Proficiency in systematic reviews, survey methods, and/or causal inference is essential, along with programming skills (e.g., in R or Python
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;Knowledge of bioinformatics tools relevant to gene editing and transcriptomics (e.g., Benchling, SnapGene, Geneious, R, Python);Proven track record in publication and in scientific outreach. Personal Skills
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/ NiFi/ Knime, Programming in Python and SQL. Experience with version control systems (Git, CI/CD); Java/Scala is a plus. Familiarity with containerisation and orchestration like Docker and Kubernetes
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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microplastic particles based on spectral and morphological fluorescence data. Develop and maintain modular analysis pipelines in Python or MATLAB, integrating data preprocessing, feature extraction, and
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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development knowledge of the state-of-the-art in climate physics and Earth system modeling and data analysis techniques programming skills e.g. in C, BASH, Python, Latex software user knowledge: MS
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skills in C/C++ and Python Relevant experience in deep reinforcement learning A proactive attitude towards achieving research excellence Demonstrated commitment, teamwork abilities, and critical thinking
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of robotics Solid mathematical foundation paired with practical robotics experience Strong programming skills in (at least one of) Python/C++ Familiarity with robotics frameworks like ROS; optimization-based