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with digital twin modelling, remote sensing, and cloud computing is valued, as is a commitment to learning and advancing in these areas. The successful candidate will have the ability to work with large
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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-mature.org and send it together with a cover letter, a curriculum vitae, a copy of all university degrees and other certificates in a single pdf-file to gerd.bacher@uni-due.de . Please mention in your
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-specific inflammation” and aims to develop and apply advanced imaging tools to study immune cell dynamics in murine models of inflammation and cancer. More about our work: https://www.medizin.uni-muenster.de
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will contribute to the enhancement and implementation of a digital model representing the Luxembourgish and cross-border energy landscape. The doctoral student will be a member of the Doctoral School
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biopsies and advanced, preclinical models. A combination of wet-lab and computational biology, close ties to the clinic, and a wonderful team of early career scientists give us the agility and expertise
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biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
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requires a dedicated individual with extensive previous research experience, in murine transgenic models and hematology. We are looking for a talented individual to carry out exciting studies in
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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control, open-source background checks may be conducted on qualified candidates for the position. DTU Chemistry is a leading chemistry department with 28 faculty, 30 postdocs, and 55 PhD students