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equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our
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application! We are looking for a research engineer within the Division of Statistics and Machine Learning (STIMA) at the Department of Computer and Information Science. In this position, you will have the
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experience in manufacturing systems modeling, simulation (i.e., DES), and digital twins. • Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production
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. We are hosted by NAISS in partnership with RISE Research Institutes of Sweden and is part of the EU’s ambitious AI Factories initiative. Learn more: https://mimer-ai.eu/about-mimer/ , https
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, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our dedicated webpage . About the research project We will recruit a
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implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation
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Computer Science, primarily within the area of machine learning. This is a temporary position at 50% during six months (the percentage and duration may be adjusted depending on starting date). For information about
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applications for a Doctoral student position in applied mathematics and machine learning for urban 3D reconstruction, within the Digital Twin Cities Centre (DTCC). The project aims to create analysis‑ready
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) processing, robotic applications (hardware/software), excellent programming skills (including lower-level languages, such as “C”), and experience in neural networks / machine learning. After the qualification
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Optimal Transport for Optimization and Machine Learning Appl Deadline: 2026/02/04 11:59PM (posted 2025/12/19, listed until 2026/02/04) Position Description: Apply Position Description Doctoral student in