126 10-phd-candidates-or-postdoctoral-researchers-in-machine-learning-and-deep-learning PhD positions at DAAD
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Description At the Faculty of Chemistry and Food Chemistry, the Chair of Theoretical Chemistry offers a position as Research Associate / PhD Student (m/f/x) (subject to personal qualification
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availability of resources, in cooperation with Leipzig University eight positions as Research Associate / PhD Student (m/f/x) (subject to personal qualification employees are remunerated according to salary
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). Tasks The successful candidate will conduct cutting-edge empirical research in at least one of the following areas natural resources and environment, climate change and policy, digitalisation, AI and
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-containing systems. Who We Are Looking For: PhD Student / Research Assistant (m/f/d) The primary focus of this PhD position is to develop and apply in situ EPR spectroscopic techniques using a newly acquired X
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collaboration, transdisciplinary cooperation with practice and an overall dynamic development characterize its research profile in the fields of education, culture, political science, management and technology as
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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with theoreticians from internationally renowned research groups. We are looking for a suitable candidate to carry out this exciting and challenging project, which will bring unprecedented information
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Description Who We Are: The Cutsail research group at Ludwig-Maximilians-Universität (LMU) Munich is seeking a highly motivated PhD student / research assistant for full-time, on-site work in the
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Researcher (PhD Position, m/f/d) Neural Circuits and Behavior This position is limited in accordance with § 2 WissZeitVG and § 72 HessHG, offering the opportunity for individual academic qualification and with
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scientific challenge. The planned PhD project will therefore investigate the interaction of food-borne toxicants with realistic co-exposure using New Approach Methods (NAMs). The focus will be