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Field
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored
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join a growing, interdisciplinary team whose projects span laboratory-level and nationally significant DOE missions. Essential Duties and Responsibilities Develop novel machine learning algorithms and
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will work in an interdisciplinary environment at the TU/e Laboratory of Chemical Biology and the Expertise Center Clinical Chemistry Eindhoven (ECCCE), a collaboration between TU/e, Catharina Hospital
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for broader clinical implementation of tumor marker assays and more reliable, minimally invasive diagnostics. You will work in an interdisciplinary environment at the TU/e Laboratory of Chemical Biology and the
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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-driven proteomic. Who are we looking for? A motivated researcher with strong programming skills and knowledge of machine learning algorithms, bioinformatics, proteomics, and molecular biology, keen to
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of an image analysis algorithm for particle tracking and speed quantification. Requirements for candidates: Essential: BSc and MSc in biochemistry, biology, biophysics, biotechnology, biomedical engineering
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optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware
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25 Sep 2025 Job Information Organisation/Company CNRS Department Institut de biologie de l'Ecole Normale Supérieure Research Field Biological sciences Environmental science Researcher Profile First
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., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware optimizations (e.g., automated pipelining). The PhD student will be supervised by Nusa Zidaric. Key