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modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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analytical programming language (e.g., Python, R) or a universal programming language (e.g., C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills
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background in applied mathematics, computational mathematics, computer science, physics, or engineering is suitable. Basic programming experience (e.g., C, C++, Julia, MATLAB, Python, or similar) is necessary
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
. Proficiency in programming and modern ML tooling (e.g., Python, PyTorch); experience with LLMs (e.g., using Hugging Face libraries) is a plus. Ability to reason about complex systems and turn ideas into code
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electrical or mechanical engineering Strong mathematical skills Experience in modelling energy systems Very good knowledge and experience in programming (e.g. Python, Matlab, C, C++) Fluent in written and
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machine learning, deep learning, or computer vision Experience with Python and common AI frameworks (PyTorch, TensorFlow) Interest in hallucination detection, robustness, trustworthiness, and (optionally
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, Management Science, Analytics and Data Science Knowledge of and practical experiences with programming (e.g., Python, Java, Julia, etc.) You must have a two-year master's degree (120 ECTS points) or a similar
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Requirements working in a Linux environment, basic Bash, scripting in Python (awk, R or other); being familiar with protein sequence and structure analyses (eg. structure prediction and docking); knowledge
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at the Doctoral School (i.e., 1st March 2026). Specific Requirements working in a Linux environment, basic Bash, scripting in Python (awk, R or other); being familiar with protein sequence and
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quantitative medical imaging Proficient programming skills in at least one object-oriented language (e.g., C++, Python) and broad understanding of common programming paradigms, including object-oriented design