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conversational guides for enhancing visitors’ learning and experiences in public educational environments. The PhD student will focus on addressing the challenge of visual blindness in large language models (LLMs
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complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including interdisciplinary communication and collaboration. You will also be offered
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environmental and life sciences challenges. Courses will cover topics such as complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including
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methods for optimized data analysis, Machine learning-based image segmentation of tomographic data (e.g., synchrotron X-ray microtomography), Design and use of autoencoders (VAEs, GANs), diffusion models
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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corresponding knowledge in another way. A successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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of quick clays. A novel combination of miniaturised thermal-hydro-mechanical experiments and particle level modelling will be pursued to unravel the unique mechanisms that make quick clays so hazardous and
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aims to build predictive and physical binding models of protein – DNA interactions using high-throughput and quantitative biochemical binding data across hundreds of thousands of sequence variants
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm