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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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, and AI-driven sensing, this PhD offers a rare opportunity to develop in-demand skills in advanced mobile robotics, intelligent automation, data fusion, artificial intelligence (AI), precision metrology
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of pathogens in the UK. We are seeking a PhD student to perform a project analysing the MScape metagenomic surveillance of infectious disease data set. We aim to recreate strain level information of pathogens
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computer science / information systems engineering. In this project, the aim is to bridge the gap between large language models (LLMs) and task automation, enabling natural language interaction, that is, via a
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11.11.2024, Academic staff In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress
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, benchmarking, and large-scale evaluation of proposed methods Publish high-quality research outcomes in top-tier international conferences and journals Collaborate with faculty, postdoctoral researchers, and PhD
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6 Feb 2026 Job Information Organisation/Company University of Oslo Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Mar
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: Applications accepted all year round Details This PhD project focuses on using topological data analysis (TDA) in machine learning (ML) to study (exotic) quantum matter systems defined on a lattice. TDA is a
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. The PhD will focus on two complementary approaches: 1) Enhancing CDI with machine learning: improve this technique using convolutional neural networks (CNNs) trained on simulated data, enabling faster and
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8 Feb 2026 Job Information Organisation/Company University of Oslo Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Mar