50 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" research jobs at Aarhus University
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-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and
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are expected to: shine in individual and collaborative research, either to assist groups of bachelor’s students in doing homework or co-teach advanced courses relevant for your research area. The
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expected to: shine in individual and collaborative research, either to assist groups of bachelor’s students in doing homework or co-teach advanced courses relevant for your research area. The Department
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computer graphics, or human vision and attention. The posts require research skills in the design of studies, use of methods, research prototyping and data analysis, and you should have documented experience
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preparation for mass spectrometry analysis in the laboratory Learning of data analysis methods and code to understand mass spectrometry data Present your data at lab meetings and (inter-)national meetings
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learning for imaging tasks Prior work with histology–imaging registration or material decomposition Clinical research exposure As a person, you have good interpersonal skills, are inclusive and team-oriented
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. Furthermore, to be highly skilled with strong learning abilities and a positive mindset, it is expected that the candidate will lead all aspects of the project. A profound interest in both the methodological
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immunostainings on cryosections, and acquire and analyse microscopy images to help assess the response of stem cells to hibernation. In addition, you will help with stem cell isolation and cell culture experiments
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on innovative learning and teaching, and research, XJTLU draws on the strengths of its parent universities, and plays a pivotal role in facilitating access to China for UK and other institutional
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skills and attention to detail Be motivated, curious, and eager to learn new methods and techniques Work well both independently and as part of an interdisciplinary research team Communicate clearly and