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Description Start date/duration 15.09.2026 for 4 years Job profile: Your tasks: Dissertation in the field of machine learning and robotics Independent research in the field of machine learning and robotics
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nanomaterials would be particularly appreciated. An interest in interdisciplinary approaches at the interface of chemistry, nanoscience, and biology is also highly desirable. Where to apply Website https
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technologies and biotechnologies to break them down. http://www.recetox.muni.cz/en/career/career-at-recetox The research group We are fascinated by glycolurils, the urea-based heterocycles, for the ability
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information at https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition Where to apply Website https://www.it.pt/ Requirements Research FieldEngineering » Electrical engineeringEducation LevelPhD
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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
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11 Jul 2026 Job Information Organisation/Company University of Twente (UT) Research Field Engineering » Electrical engineering Engineering » Mechanical engineering Researcher Profile First Stage
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cohort of doctoral researchers and benefit from ReDiLEEP training in response diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation
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carried out free of charge, at universities or research institutions, both Italian and foreign, other than the University of Pisa. Where to apply Website https://pica.cineca.it/unipi/ Requirements
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PhD thesis student (f/m) at ESRF and University of Bath to study CO₂ capture by coupling X-ray Raman
University of Bath’s English language entry requirement (https://www.bath.ac.uk/corporate-information/postgraduate-research-degrees-english-language-requirements-for-international-students/ ). If the applicant
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focus on combining simulations using spatial-genetic-demographic individual based models (e.g., using the software SLiM), machine learning approaches, and genomic data to estimate larval dispersal