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collaborations, we are a key force in the field. Our core competencies include in vitro ADME models, advanced in vivo methods, computational modeling and simulation, as well as patient-focused and policy-related
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of implant surfaces functionalised with antimicrobial peptides (AMPs) using experimental infection models to assess the biocompatibility and therapeutic potential of AMP-coated titanium and polymers in
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processes with relevance for irrigation and drainage Have knowledge in programming in R and Python for statistical analyses and modelling. This includes experience in applying these skills in projects Have
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to this third-cycle studies which corresponds to four years. Position description We are seeking a PhD student to join our research team specializing in the analysis and modeling of multiphase flows. The research
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Python for statistical analyses and modelling. This includes experience in applying these skills in projects Have knowledge and experiences in using HecRas, SWAT and ArcGis Pro Experience in designing and
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trustworthy and factual language models. Host of the largest basic research program in Sweden Wallenberg AI, Autonomous Systems and Software Program (WASP) as well as the Wallenberg AI and Transformative
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is on analysing first-person descriptions of conscious experiences with the help of machine learning and large language models (LLMs) to identify, compare, and systematize different types of states of
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essential tool for training and testing of AI models and control systems for robots and autonomous vehicles. In a digital environment, large amounts of annotated training data can be created safely and easily
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essential tool for training and testing of AI models and control systems for robots and autonomous vehicles. In a digital environment, large amounts of annotated training data can be created safely and easily
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this, we focus on self-supervised denoising, where models learn to restore images using only the noisy data itself — without requiring clean references. Existing approaches often rely on convolutional neural