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Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau | Landau in der Pfalz, Rheinland Pfalz | Germany | about 18 hours ago
with recognized expertise in environmental modeling/ environmental data science. We therefore welcome applications that complement our existing portfolio in an integrative manner. The successful
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Your Job: Chromatography modeling, while crucial for modern bipporcess development, still heavily relies on empirical determination of key model parameters. By combining protein structure
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have: Ph.D. in Biostatistics, Statistics, Bioinformatics, Data Science, or related field; with (i). technical skills such as Proficiency in R, Python, or SAS for statistical analysis and modelling; (ii
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change. To apply, visit https://northeastern.wd1.myworkdayjobs.com/en-US/careers/job/Boston-MA-Main-Campus/Postdoctoral-Research-Associate--Translational-Muscle-Biology--Murine-Models-_R138320 Copyright
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to early-stage efforts focused on muscle biology and inflammatory disease. The successful candidate will apply their expertise in murine models and immunology to explore disease mechanisms, validate novel
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/InstituteVIBCountryBelgiumCityLeuvenPostal Code3000StreetHerestraat 49Geofield Contact City Leuven Website https://jobs.vib.be/j/130090/postdoc-position-deep-learning-for-glioblastoma-sequence-to-function-models Street Herestraat 49 Postal
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: Master's degree in Economics in Computer Science and Econometrics or a graduate with a specialization in Business Intelligence, knowledge of advanced econometric modeling and statistical methods, programming
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related field. Demonstrable expertise in foundation models / large language models, multimodal modelling, or agentic / multi-agent systems is essential. Experience or strong knowledge of causal discovery
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The Multiscale Materials Modelling Group at Maynooth University invites applications for three fully funded PhD positions focused on the design of advanced polymer-hybrid anion-exchange membranes using multiscale
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics