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. The candidate should have a strong background in computational biology or a related field. They will: Work closely with the clinical partner to understand the unmet clinical needs. Integrate the existing datasets
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submit these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-position-in-computational
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interdisciplinary project on the development of new computational approaches for improving safety and sustainability of (nano)materials based on publicly available data and tools, including omics data, and
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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in Mechanical or Aerospace Engineering, Physics, Computational Science, or a related discipline. The candidates should have: Solid programming skills (Python, MATLAB, or C++). Knowledge of the OpenCV
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to support a circular bioeconomy. We are seeking a highly motivated postdoctoral researcher to develop and apply machine‑learning and data‑science methods, with a focus on computer vision, to enhance wood
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of Computational Fluid Dynamics CFD environment and simulations including: - Computation of the microwave field, Coupling of the microwave field with the plasma - Computation of elementary ionization, recombination
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varied responsibilities in a dynamic, nationally and internationally oriented research environment Access to state-of-the-art experimental and computational infrastructure Attractive employment conditions
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work with rich datasets, advanced analytical tools, high-performance computing infrastructure, cutting-edge photonic sources, and modern industrial machinery. In this position, you will contribute
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Network with 15 funded 3-year PhD positions in parallel. Your profile Master Degree in environmental/natural sciences or engineering, or similar. Experience with developing computational models Preferably