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– Adaptive & Agentic AI. The PhD project focuses on developing robust and reliable machine learning systems that can adapt at test time under real-world distribution shifts. Modern foundation models (e.g
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Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including data attribution, data curation, and privacy preservation for large foundation models (e.g., LLMs and VLMs
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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! ESRIC is conducting activities in three main areas: Research and testing facilities, Business support and incubation, and Community management. The primary objective of ESRIC is to research, develop and
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involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build more trustworthy and robust AI models that can
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-throughput experiments in molecular biology, image and video analyses as well as pattern recognition of complex public health data Collaboration in the development of algorithms/methods and development
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we live in. Your
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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The Computational Protein Engineering (CPE) group at The Novo Nordisk Foundation Centre for Biosustainability (DTU Biosustain) is developing novel methods to engineer proteins more effectively using