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SD-26045-RESEARCHER IN ADVANCED PLASMA-ASSISTED DEPOSITION PROCESS DEVELOPMENT FOR CATALYTIC THIN...
photoelectrochemical applications. The project targets the synthesis of metal oxide-based thin film materials, with a strong emphasis on process design, optimization, and integration through the coupling
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safety-critical domain, reducing hallucinations and improving robustness and trustworthiness are essential. This PhD targets principled ways to detect, analyze, and mitigate hallucinations in video-based
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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among the top 10 European departments based on the number of top economics, finance, and mathematical statistics publications per professor over the last 5 years. It provides an international and
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nutrients with the soil through adaptive root and fungal networks. The successful candidate will design and implement a modelling framework based on Partial Differential Equations (PDEs) to represent
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Designing hierarchical graph‑based models to predict toxicity under uncertainty by linking molecular‑level and system‑level knowledge Advancing causal inference methods to predict transformation products
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based on Partial Differential Equations (PDEs) to represent the coupled dynamics of roots, mycorrhizal fungi and soil resources under varying environmental conditions. The work will integrate concepts
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for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability. Applications will be continuously reviewed
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-based numerical and statistical tools Language skills • Fluency in English, both oral and written. Skills in French is an asset. Your LIST benefits · An organization with a passion for impact and
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
compositions of Ti and C and different structures, including MD-based nanoindentation simulations and defect analyses. To facilitate this, you will further develop the ultra-fast machine-learning potentials used