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modelling methods to design resistance-proof antibiotics. You will join an interdisciplinary team, integrating machine learning, medicinal chemistry and microbiology. You will work with Asst. Prof. Eli N
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computational datasets of disordered materials based on density functional theory calculations and training machine learning models to accelerate the predictions. This work will involve collaboration with Assoc
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Professor Kilian Huber (University of Chicago) to implement new AI methods for the study of firms’ cost of capital based on textual analysis. The project uses large language models and other AI tools
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Job Description At DTU Energy we are looking for a postdoc to work on modeling and designing a novel type of heat exchanger equipped with thermoelectric generators, to recover and convert waste heat
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Postdoctoral Researcher with a strong computer science background and demonstrated expertise in deep learning and generative model development to lead the AI component of this initiative. Responsibilities and
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building materials using polyphasic detection and identification approaches. Characterization of biobased building materials with respect to their moisture sorption isotherms. Modelling the correlation
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
The Department of the Built Environment (BUILD) at The Technical Faculty of Engineering and Science invites applications for a position as PostDoc in the field of material science, modelling and
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at the single-atom level Understanding of atomic mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. 4. Modeling Atomic Processes on Nanoparticles You
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enable us to test Risø HPP when it is connected to different electrical power grids, which we will emulate with the CGI. We are looking for a Postdoc who will be engaged in experimental research and model
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
research task is to model semantic change and conceptual structure using Natural Language Processing. We will build customized NLP pipelines for premodern Greek and humanistic Latin, train and evaluate word