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Job Description Are you worried about the coastal regions in an era of climate change and plastic pollution? Do you want to play a part in the development of a novel numerical model that can shed
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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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(2026–2029) focused on creating digital twins and AI-driven models for solid state quantum devices. The position is placed in the Theory & Simulation and Data teams of NQCP. Role Description We
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microscopy to generate new insights into how cells coordinate and repair DNA double-strand breaks? Using baker’s yeast, Saccharomyces cerevisiae , as a model organism, the project is designed to uncover novel
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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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tools or functional genomic information or OMICS to improve genomic prediction models. The persons hired will collaborate with industry partners, teach at undergraduate and graduate levels, and supervise
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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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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Postdoctoral Positions in PFAS Analytics, Degradation, and Thermophysical Properties - DTU Chemistry
thermophysical properties vary across the diverse PFAS chemical space and how these properties may be predicted using computational models. These positions offer an excellent opportunity for early‑career
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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