10 developer-"https:"-"https:"-"https:"-"Keele-University" research jobs at University of Antwerp
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Department: Product Development Regime Full-time Let’s shape the future - University of Antwerp The University of Antwerp is a dynamic, forward-thinking, European university. We offer an innovative
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objectives: 1) conceptualizing legal creativity, with the aim of understanding what legal creativity is; 2) measuring legal creativity by developing a valid and reliable measurement tool; and 3) developing
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photoelectrochemistry and nucleic acid detection. Ultimately, the project may contribute to the development of novel biosensor technologies for detecting clinically relevant nucleic acids in healthcare applications
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part in the instrumentation developments related to this facility in Maastricht. The University of Antwerp is also one of the initial founding research units of the Einstein Telescope Collaboration
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developments that have implications at the intersection of human rights and ethics/philosophy of law. You will develop new research projects according to the strategic plan of the Personal Rights and Property
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will assist in the development of teaching methods, teaching and study materials, evaluations, etc. You will supervise students working on their Bachelor and Master dissertations. Services You will play
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anatomical analysis. The core scientific objective is to develop a unified pipeline that integrates generative AI, statistical shape modeling, and biomechanical soft tissue modelling to enhance anatomical
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(project idea & CV) acquire a preparatory post-doctoral research mandate to further develop and submit a competitive research proposal to FWO (Flemish Science Foundation) or MSCA (Horizon Europe Marie Curie
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Infrared Spectroscopy) and rheological assessment (i.e., Dynamic Shear Rheometer) of bituminous binders is a nice-to-have. You are keen on developing new knowledge in multivariate statistics and modelling
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predictive microstructure imaging with MRI. Within the ADAMI project, you will help develop an innovative approach to predict the cellular composition of brain regions in MRI datasets based on in toto light