873 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Sweden
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Field
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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral
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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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. Please visit the following homepage for more information on the Department: https://www.slu.se/en/about-slu/organisation/departments/Animal-Biosciences/ Read more about our benefits and what it is like
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/tensions between the global North and global South. We will also consider applicants focused primarily on Swedish/Nordic cases or topics. For full information of the five REMESO research streams see: https
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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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highly interdisciplinary setting combining microbial mutagenesis assays, mammalian cancer models, next-generation sequencing, bioinformatics, and machine learning. Experimental data will be integrated with
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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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employees and is characterised by a friendly, inspiring and international atmosphere, with a large number of employees from all over the world. The PhD student will be included in Machine- and Materials
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a strong constellation of both traditional applied biostatistics and expertise in artificial intelligence and machine learning, which is undergoing rapid development. The clinical activities
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration