26 algorithm-development-"Multiple" "NTNU Norwegian University of Science and Technology" positions at Linköping University
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multiple subfields represented, including animal behaviour, evolution, ecology, genetics, zoology, conservation, microbiology and animal welfare. See: https://liu.se/en/organisation/liu/ifm/biolo
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research, undergraduate and postgraduate education within the field of biology, with multiple subfields represented, including animal behaviour, evolution, ecology, genetics, zoology, conservation
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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prominent approach to AI, with impressive performance in many application domains, including materials discovery. This development has a huge potential for societal impact, with applications in renewable
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RNA-seq data from single cells. For this, you need to be proficient in using existing tools for bioinformatics analysis. The work is varied, and there are great opportunities for personal development
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We are seeking a highly motivated and talented postdoctoral researcher to join our team in developing novel organic bioelectronic electrodes for interfacing with the nervous system. This position is
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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application! Work assignments The purpose of the position as an assistant professor is that the teacher should be given the opportunity to develop his independence as a researcher and to merit both
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Pharmacology (KKF). The overall aim of the project is to develop improved diagnostic and predictive tools for hematology and clinical immunology. The project is a collaboration with Sofia Nyström ’s group