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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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Gifts ”. The project is led by Dr. Isabel Z. Martínez at ETH and Prof. Marius Brülhart at University of Lausanne. Aurélien Eyquem (HEC Lausanne) and Enrico Rubolino (HEC Lausanne and CREST Paris
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sequencing and researching disease in patient cohorts, working with machine learning techniques and programming computers. The candidate will learn about different flavors of metagenomic sequencing, how
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: Data Mining Machine Learning Bioinformatics The successful candidate will contribute to advancing state-of-the-art in data mining and machine learning research with applications in computational biology
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programme , and is led by profs. Alexey Lyulin, Heiner Friedrich and Henk Huinink (all TU/e) and prof. Bernard Geurts (U Twente). The project explores how waste products can be turned into a sustainable
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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This project fuses machine learning (ML) based inverse design approaches and topology optimisation (TO) to realise multiscale
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts