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Field
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(sequence homology- or protein structure-based) Familiarity with UNIX/LINUX-based operating systems and shared compute infrastructure Proficiency in Python, R, or similar languages for data analysis
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of testicular tissue Validate gene expression at the protein level via IHC and Western blotting Analyze large-scale transcriptomic data (R, Python) Test allele-specific regulatory activity using luciferase
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Infrastructure resilience under multi-hazard scenarios Model development and data analyses includes writing well-documented, reusable code (Python or R) Collaborate closely with fellow PhDs and project partners in
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g
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proficiency in Python and experience with ML/DL frameworks like PyTorch or TensorFlow Strong analytical and communication skills, creativity, and the ability to work independently while collaborating in a team
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experience of programming (e.g., Python, C#, C++). Ability in teamwork and to work both independently and in groups. English language proficiency. Personal characteristics such as structured approach
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· Programming skills in Matlab, R, and/or Python · Experience in the organisation of field campaigns Language skills · Fluency in English, both oral and written. Your LIST benefits
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices
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, Computer Science, Mathematics, Physics, or related field; Strong interest in cardiovascular physiology and computational modeling; Programming experience (preferably MATLAB, Python, or similar); Enthusiasm
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and image analysis (MATLAB or Python), machine learning techniques, and basic programming/coding will be a plus. Fluency in English is mandatory. Willingness to work in an inter-cultural and