551 algorithm-development-"Multiple" "NTNU Norwegian University of Science and Technology" PhD positions in Germany
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, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic programs
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oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
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: 01.10.2025 Application deadline: 03.09.2025 Tasks Execution of experimental work in a mouse model of cortical multiple sclerosis Application of in vivo imaging and quantitative analysis methods Investigation
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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technology. ▪ Close connection to the activities of the Munich Quantum Valley with its main goal to build a quantum computer based on different platforms, to develop suitable algorithms and applications, and
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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applications of data science and artificial intelligence. In addition, service-oriented solutions are developed and there is close cooperation with a large number of partner organizations from science and
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interdisciplinary, and there are multiple aspects to it that one or two different persons can fill with different interests/backgrounds. In all cases, extensive project training will be provided. Candidates with
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science