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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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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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materials, catalysis and/or surface science. For Topic 4, candidates must have documented skills within computational modelling of atomistic processes. Experience in scientific programming, e.g. using Python
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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
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generation Developing and optimizing generative models for de novo binder design Collaborating closely with wet lab scientists who will express and test the designs that have been created Developing scalable
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models. Your primary tasks will be to: Development and optimisation of nanoformulations for cancer therapeutics Physicochemical characterization of nanomaterials using FTIR, DLS, TGA, sp-ICPMS, TEM, SEM