56 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" research jobs at Technical University of Denmark
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Job Description If your background is in machine learning (ML) and you have a desire to make discoveries in health sciences, then this position as Postdoc is your possibility. In this collaboration
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at the top venues of machine learning research. Responsibilities and qualifications You should have prior experience with machine learning from both a theoretical and practical perspective. Experience in one
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and engineering optical setups Experience with coherent control of quantum systems Competence in electronics design and hardware control Ability to acquire and process large datasets Enthusiasm
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related field, with a strong focus on autonomous systems. Demonstrated research expertise in one or more core areas of AI for autonomy, such as: Robot control and learning-based control; Decision-making
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research for the tenure track period CV including employment history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience
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deliverables with high standards of accuracy and clarity. Teach and supervise BSc and MSc student projects, and be co-supervisor for PhD students We are looking for candidates with: Skills in molecular biology
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within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer
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Postdoctoral Positions in PFAS Analytics, Degradation, and Thermophysical Properties - DTU Chemistry
may be obtained: From Professor Charlotte Held Gotfredsen, tel.: +45 20650942, email: chg@kemi.dtu.dk with respect to position 1 and 2. Website: https://www.kemi.dtu.dk/english/research/organic
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of strains) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modelling
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about DTU Electro at www.electro.dtu.dk . For more specific information on the Quantum Light Sources group, see also https://electro.dtu.dk/research/research-areas/nanophotonics/quantum-light-sources