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Field
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globally having access to large (>10,000 patients) matched multimodal data across radiology, pathology and molecular profiling and clinical data. Machine learning methods hold the potential to advance
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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, antennas, and electromagnetic metasurfaces. The computer-aided simulation of electromagnetic fields is critical in the design of most computing and communications devices, such as high-speed interconnects in
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delivered in routine practice for people with alcohol and drug dependence. This will be a large-scale longitudinal cohort study using national registry data on employment and health. A target trial emulation
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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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patients Experience with clinical data collection Familiarity with epidemiological methods and registry-based research, epigenetic analyses or machine learning. Interest or experience in science
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. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer science, or possibly design or cognitive science as main subject) and one at Tema Technology
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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: WP1 will analyze large-scale registry data from the Nordic countries and England to assess the safety of modern ASMs. WP2 will investigate genetic, epigenetic, and pharmacological markers of ASM-related
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on