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Additional information on beginning, duration and mode of study The starting date of the PhD project is flexible. The initial funding period is usually three years. Find out more at https://www.bgc-jena.mpg.de
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 1 day ago
supervision Yes Research training / discussion Yes Career advisory services and programmes for future professionals The BTU Career Center (https://www.b-tu.de/en/careercenter ) offers extensive support to
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to fill the position of a Researcher (m/f/d) – Text Mining for Biodiversity Knowledge (Entomology and Legacy Texts) full-time / part time Location: Müncheberg (Brandenburg) Employment scope: full-time
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conceptualize a proof of physical work protocol focusing on technical aspects Sustainability analysis. You investigate physical mining and quantify its CO₂ footprint Scientific communication. You publish your
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, using techniques such as: High-dimensional data mining Tensor decomposition Causal inference Statistical process modeling Machine Learning Applications include public transport, private vehicles, traffic
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found here: https://doi.org/10.1002/advs.202409386 Your Tasks Experimental research. You develop and test potential physical one-way functions in collaboration with international partners Protocol design
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ontology alignment in physics and materials domains Build and maintain ontologies, OWL/RDF knowledge graphs, SPARQL endpoints, and open benchmarking suites to guarantee FAIR, reusable research data Mine and
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 4 days ago
on our websites: https://www.b-tu.de/en/international/international-students/help-advice-on-all-aspects-of-studying/scholarships-1 . Academic admission requirements Applicants must possess a MSc (or
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-Checking, Argument Mining, Automated Planning, and Decision-Making. Training, domain adaptation, and evaluation of cutting-edge LLMs and Multi-Modal models in the cloud and on premise. Software Engineering
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools