183 machine-learning "https:" "https:" "CMU Portugal Program FCT" Postdoctoral positions in Denmark
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background in bioinformatics, machine learning, single-cell omics, statistics, or genomic medicine, and a keen interest in obesity, diabetes, and cardiovascular disease. Background The Novo Nordisk Foundation
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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Job Description Are you burning for physics and how to teach it? Do you want to be a central part of developing new lab exercises for teaching quantum mechanics and electromagnetism at university
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highly desired. Strong communication skills, the ability to collaborate effectively within the team, and proactive working style are essential. The candidate should be motivated, open to learning new
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-motivation to learn. Have the ability of working independently. Have a strong sense of responsibility. Research environment The candidates will be integrated in the unit SDU Robotics, part of the Maersk Mc
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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University (http://bio.au.dk/en) and work in the Section for Microbiology at this department. The section employs 12 permanent scientific staff and ~20 PhD students and postdocs. Research at the section covers
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students. The department is responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk/ for further information
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strives to put knowledge into action by: Engaging partners in the co-creation of knowledge, learning and social change. Empowering our students to become reflective and responsible citizens who have the
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, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and