49 machine-learning "https:" "https:" "https:" positions at Chalmers University of Technology
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at the division of Computer and Network Systems , where we design secure, dependable and high-performance computer and communication systems that meet the demands of an increasingly digital and interconnected world
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods. Special
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conducting research "in the wild" (e.g., field deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an
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your application: Experience in system identification and machine learning is a merit. What you will do Perform research, developing your own scientific concepts and communicating the results of your
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(e.g., from the viewpoint of physics, chemistry, or mechanical engineering), programming, machine learning, or equipment automation (including microfluidic systems, robotics and remote sensing
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the last three years prior to the application deadline. Experience in some of the following areas is meritorious: AI and machine learning; convex analysis; functional analysis; mathematical statistics
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, or quantum-inspired methods Experience with hybrid quantum–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience
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, such as pulse design or numerical optimization Background in data-driven or machine-learning approaches relevant to optimal control (e.g., model learning, reinforcement learning) What you will do Take
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to the forefront of quantum technology, and to build a Swedish quantum computer. Building a quantum computer requires a multi-disciplinary effort involving experimental and theoretical physicists, electrical and