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Field
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g
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Applications are invited for a 4-year PhD position in Biostatistics, in a project on causal inference for the effects of vaccines and other pharmaceuticals, at the Oslo Centre for Biostatistics and Epidemiology
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interested in doing causal inference in policy-relevant research, and working with large administrative data. Job requirements We welcome PhD candidates who aspire a career in research. To become one of our
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of error-controlled biomechanical models in SOFA / FEniCSx / SOniCS for real-time use on AR devices Design of Bayesian neural-network surrogates and graph-based models for tissue deformation and brain shift
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of advanced language models and derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable
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University of Oslo. Place of work is the Department of Biostatistics (OCBE), Domus Medica, Gaustad UiO campus, Oslo. Job description The position is connected to the project “Bayesian Enhanced Tensor
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low-dimensional systems , Quantum Transport in topological phases , Radiation Therapy Simulation , RF Engineering , Scattering amplitudes , simulation-based inference , single- and multicomponent
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attributes and tasks. The value of such models should then be demonstrated by informing training and inference processes. A range of different strategies can be explored, including new ways to derive model
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encompasses model compression and optimization for edge deployment on UAV-mounted processors to support real-time inference. The candidate will collaborate with industrial partners for real-world data
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sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background Cardiovascular Magnetic Resonance (CMR) plays a central role in the non-invasive