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Field
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using data-driven methods You do not need to be an expert in machine learning at the start of the PhD, but you should be keen to develop rigorous ML and software engineering skills alongside deep
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. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in R and/or
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systems, thermal energy storage, data-driven building control systems and other novel solutions for the urban built environment sector. This position is to recruit a member of the research team to work on a
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modelling, data-driven approaches, and experimental validation. The project combines computational materials science with practical membrane design for electrochemical energy applications. PhD Position 1
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public health. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in
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27 Jan 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Modelling tools Computer science » Programming Engineering » Civil
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Dortmund, we invite applications for the Research Group Analysis of Microscopic BIOMedical Images (AMBIOM): PhD Candidate (m/f/d) The position is part of the DFG-funded project: ComplexEye - a 96/384-well
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at least one relevant technical domain. Strong software engineering skills and familiarity with collaborative development practices. Ability to work closely with researchers and translate between
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the team. Each position will address a complementary research area within the project: 1. Quantum Control and Reinforcement Learning (CINN, Asturias) Develop AI-driven control strategies based
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interaction, advanced numerical modelling, experimental techniques, sensor development, data-driven methods, and artificial intelligence for industrial applications in energy, process, and materials engineering