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of written and spoken English. You should have experience with programming (e.g. Python, Julia), simulation methods (e.g. molecular dynamics) and modern machine learning methods. Additional Information
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own learning. You should apply if First degree in Engineering, Applied Mathematics or Physics (with an MSc or PhD in a related topic). Experience of processing of numerical and/or experimental data and
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skills and experience: Essential criteria PhD or equivalent (or thesis submitted*) in at least one of the following subjects: Computer Science, Machine Learning, Biomedical Engineering, Medical Imaging
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15 Jan 2026 Job Information Organisation/Company IFP Energies nouvelles (IFPEN) Research Field Engineering » Mechanical engineering Researcher Profile First Stage Researcher (R1) Positions PhD
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beneficial: Working knowledge of statistics and usage of MATLAB or other software for statistical analysis; Experience with machine learning and data mining. Good Estonian language skills Application procedure
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. This PhD position focuses on the design of novel computer architectures to enable large AI models to run on embedded and edge systems under strict timing, energy, and memory constraints. Current solutions
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 days ago
PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis or machine learning, proficiency in deep learning techniques (CNN, VIT
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) Chalmers/University of Gothenburg drives cutting-edge research in machine learning and its application within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties
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of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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. The project will provide the student with extensive training in large-scale data integration, machine-learning methods, field-based environmental monitoring and eDNA analysis, as well as experience working