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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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. - Experience in flow diagnostics (e.g., PIV, load measurements) and/or vortex or mid-/high-fidelity aerodynamic simulation tools. - Good programming skills (e.g., Python, MATLAB). - Ability to work both
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independent research interests. Your profile Required: PhD in Marketing/Business/Analytics (or a related field); strong statistical background; proficiency in Python; fluent English. Preferred: experience with
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experience in Python and/or C++ Strong mathematical and analytical skills Has experience working collaboratively within a multidisciplinary team. Excellent oral and written communication skills as demonstrated
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, or photochemistry Experience building optical setups Experience in performing steady-state and time-resolved spectroscopy measurements Proficiency with Python or Matlab Excellent scientific writing and communication
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++, Python), and data analysis. Familiarity with ultrasound imaging and medical signal analysis is highly desirable. Excellent written and oral communication skills, and the ability to work collaboratively in
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in python programming and machine learning models for molecular discovery and chemical property prediction. For informal enquiries, please contact Dr Martin-Martinez at francisco.martin-martinez
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Intelligence, or a closely related field Solid experience in one or more of the following: NLP, speech processing, human-AI interaction, or agentic-AI systems Strong programming skills in Python and familiarity
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, biostatistics, or a related discipline. Expertise in human genomic and transcriptomic studies and a strong interest in neurodegenerative disorders. Programming experience, preferably in Python or R, and
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) Programming: Python, version control (Git), comfort with reproducible workflows/CI What we offer We offer a full-time position as an academic staff member and a central role in a DFG Research Unit at the