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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | about 1 month ago
new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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Omer Ben-Neria Logic, set theory Shai Evra Graph theory, representation theory, number theory Adi Glucksam Complex analysis, potential theory, and dynamics Or Hershkovits Geometric analysis
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Internal Number: 6976513 Biostatistician Brown University To view the full job posting and apply for this position, go to: https://brown.wd5.myworkdayjobs.com/en-US/staff-careers-brown/job/155-South-Main
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License: No If yes, what is the preferred licensure/certification?: Preferred Computer Applications: Preferred Other Computer Applications: Graphing software Preferred Additional Knowledge, Skills and
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-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2026/phd-position-in-hierarchical-graph-n… Requirements Research FieldComputer scienceYears
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molecular level. To yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and
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developing knowledge-graph or information retrieval systems. Funding & Appointment Terms The appointment provides full financial coverage through a dedicated fellowship, comprising: Monthly stipend of €1,650
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percent of its 25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory to medieval literature and blind rehabilitation. Of 101 graduate
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at the University of Twente is looking for two PhD candidates to join the research team of Dr. Gaurav Rattan. The positions are funded by the NWO VIDI project Learning on Graphs: Symmetry Meets Structure (LOGSMS