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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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, preparing graphs, tables, and charts, etc. Conducts literature searches to develop insights into the significance of experimental results and to acquire information on new or improved methods, procedures and
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. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored
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interdisciplinary and to learn new skills and to perform research in collaboration with others. We seek candidates with the following qualifications: A doctoral degree in a Bioscience-related field awarded
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data, MRI data, and other types of data. Contribute to projects at LCBC with data analysis, development, and implementation of advanced machine learning models. Write and publish scientific articles
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, China [map ] Subject Areas: Biophysics / Active systems; Multicellular systems Physical Biology Appl Deadline: 2025/07/31 11:59PM (accepting applications posted 2024/10/22, listed until 2025/07/31