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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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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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. 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 | 1 day 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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. 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
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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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in the new Lab42 building at the Amsterdam Science Park. The VIS Lab performs research on deep learning and computer vision, from hyperbolic learning to medical imaging and from NeuroAI to foundation
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sound understanding of data evaluation Prior experience with single-cell data analysis, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently
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science/statistics/applied mathematics/electrical engineering can also be considered given that the candidate has formal competence in machine learning and/or image analysis/computer vision Foreign completed degrees
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological