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At the Technical Faculty of IT and Design, Department of Electronic Systems, one or more PhD stipends/Integrated PhD stipends in representation, compression, learning, and inference for classical
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, compression, learning, and inference for classical and quantum data exchanged through classical and quantum networks. The objective of the PhD study is to explore and address research and design challenges
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features enhance binding to the receptors. This information will be carried forward to human tasting panels. You will also investigate how other components of food matrices inhibit binding. You will thus
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sequences, analyse those data using Bayesian, Maximum Likelihood and coalescence approaches, and build matrices of geolocation and morphological data. The work will be alongside others working on related
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HPLC-MS, GC-MS experience in the extraction of natural compounds from complex matrices knowledge of the isolation and structural elucidation of natural products experience in the statistical analysis
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pressure shock waves which induce compressive residual stresses in the structure, thereby improving the surface hardness and the resistance to fatigue cracking and to corrosion. LSP is more effective than
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generating volatile compounds in algae, as well to unravel their dependance on different food matrices. Results of the project will boost diversification of our food system, stimulating algae as a sustainable
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wide range of sample matrices. We offer creative and stimulating working conditions in an international research environment. Our research facilities include modern laboratories and advanced analytical
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starlight. In ICE-EEVOLVE , we seek to unravel how chiral organic molecules, trapped in amorphous ice matrices, evolve from molecular clouds through star-forming regions to planetary systems. Laboratory
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) light source that can suppress spurious nonlinearities in direct drive fusion target compression. As part of the IGNYTe team, you will develop a laser comprised of a shapeable incoherent fibre front