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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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photoreceptive pathways using mouse as a model system. Methods used in the lab include various in vitro, ex vivo and in vivo approaches, as well as functional and behavioral studies of relevant opsin knockout mice
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of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
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scaling and generalization behavior Roll out the model to the global user community Requirements PhD or MSc in computer science, physics, mathematics or a related discipline Experience with large-scale HPC
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new in-house data, thereby continuously improving predictive accuracy Establishing potency models using a range of different Computational Chemistry methods What potential solutions would be out
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, or landscape modelling Further, we will prefer candidates with some of the following qualifications: Teaching and supervision experience at the BSc and MSc level Interest and preferably experience in developing
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information see https://www.kuleuven.be/personeel/jobsite/jobs/60473129 Job description Design and implement chemometric and machine learning models (e.g., PCA, PLS-DA, clustering, CNNs) to classify
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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to integrate various structural biology data (NMR, SAXS, FRET, EPR) as well as computational models and simulations to create and interpret conformational ensembles of disordered protein regions, with the goal
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within