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Field
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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correlation structures across data modalities that relate to outcomes such as survival and treatment response. Validation & Benchmarking: Apply the framework across cancer types, evaluating various foundation
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cyanobacteria and Paramecium bursaria. Image data analysis using AI-based tools and programming analysis scripts. Participation in conferences, presentations, and preparation of publications. Intensive exchange
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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. The student will perform ‘big data’ analysis of patient cohorts including time-based evaluation of the impact of introducing CT-FFR as a national health intervention into a healthcare system. Exploratory
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geospatial data on fisheries activities near OWFs to evaluate the distributional impacts of OWFs across different fleet segments; conducting fieldwork and surveys in collaboration with ‘NO REGRETS’ partners
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This large-scale ecological project investigates the barriers and drivers of post-fire forest recovery. With climate change and the spread of forest fires to new areas, it is important to
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research opportunity focuses on advancing large-scale additive manufacturing using metal wire as feedstock and electric arc as the heat source. The project aims to develop an innovative and efficient method
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team of researchers using operational and information-theoretic tools to gain insights into quantum foundations, causality, and space-time physics. We are convinced that further progress on open problems