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Field
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(mammalian cell cultures) and whole tissue level (preclinical cancer models). Main Tasks and responsibilities: The PhD candidate researcher will focus primarily on laboratory-based experimental work in the
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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immune cells in cell culture and murine models of inflammation and cancer Collecting, analyzing and annotating MRI data Combining MRI and mass spectrometric imaging data in data base for quantitative MRI
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for Additive Manufacturing of the Biomaterials and Tissues of the Future. You will be one of 17 doctoral students across the entire network, and one of three doctoral candidates based in this particular research
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of TrustLLM a large EU project developing trustworthy and factual language models. Host of the largest basic research program in Sweden Wallenberg AI, Autonomous Systems and Software Program (WASP) as
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of the anti-MMP9 Nano-antibodies in a mouse model of delayed healing and a 3 weeks training at Nordic Bioscience( Herlev, Denmark) in the team of Dr. Signe Holm Nielsen to establish a Nano-antibodies based
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model-based control tailored to systems like NudgeFlow. The framework decomposes the global control problem into smaller local problems for each zone or room, enabling independent optimization with local
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children with autism and eating behavior challenges. This research explores how large language models (LLMs), interactive robotics, and multimodal technologies can support creative expression and
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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university degree (diploma, master's degree) in transport or traffic flow or related study programs. Solid knowledge of at least one programming language, preferably Python, experience in model-based