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for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling
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about biology and interested in building new machine learning and AI to accelerate biological discoveries? Then this position is for you! Join Us! We are looking for a motivated PhD candidate to develop
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this PhD project, you will build a self-driving laboratory platform that will help solving outstanding questions at the forefront of (photo)chemistry by implementing automated spectroscopy workflows
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a biological reference point for identifying disease-specific biomarkers. A central part of the
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, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools to the setup Create and validate reproducible automated workflows
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what you are going to do Design and build flow setups using 3D printer, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools
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Are you a highly-motivated researcher looking for a PhD position in complex dynamical systems and want to make some impact? If yes, the analysis group of the Korteweg-de Vries Institute
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countries (HIC). The airm of this PhD project is to understand how E. coli colonization contributes tot he risk of diarrheal disease and infections with AMR and use this knowledge to design interventions
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chemistry and study the physicochemical properties of peptides loaded into the materials. Build surrogate models and apply machine learning techniques to extract design rules and rapidly screen thousands