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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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simulations to analyze and optimize hemodynamic parameters in CAD-related applications. Collaborate with clinicians to translate simulation insights into practical solutions for cardiovascular health. Develop
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intelligent transportation systems (ITS). Proficiency in programming, traffic simulation, statistical modeling, and machine learning/deep learning techniques. Excellent communication skills. Ability to work
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/nanofabrication, l’électronique de puissance, l’encapsulation et l’intégration électroniques. • Expérience avec les outils de simulation numérique et les outils de calculs : Ansys HFSS, Matlab etc. • Fort intérêt
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/nanofabrication, power electronics, electronic packaging and integration.• Experience with numerical simulation and analytical computation tools: Ansys HFSS, Matlab etc.• Strong interest in multidisciplinary
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/nanofabrication, power electronics, electronic packaging and integration.• Experience with numerical simulation and analytical computation tools: Ansys HFSS, Matlab etc.• Strong interest in multidisciplinary
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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copy of your MSc and BSc degree certificates, including transcripts of all MSc and BSc university records (grades and courses) and their English translations (Finnish and Swedish certificates are also
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework