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transporters. These studies involve the identification and characterization of channels and transporters in T and B lymphocytes, investigation of the molecular mechanisms by which these ICTs control cell
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modelling; repeated-measures or longitudinal intervention data; randomized controlled trials or intervention research; open science practices. Teaching The position includes a 20% teaching obligation
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grant project “Driving innovation in crop resilience through Comparative QTLomics.” The selected candidate will contribute to five main objectives: 1. Apply large language models (LLMs) to collect
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Engineering. The position is closely connected to our activities within developing high-fidelity models that capture the coupled thermal, chemical and electrochemical phenomena governing system performance
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more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world
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thereafter. Explaining complex AI models is a key challenge for ethically responsible AI. Explainable AI (XAI) research aims to provide relevant information to assist developers and users in analyzing AI
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Do you enjoy finding solutions to integrate and analyse large data sets of biodiversity dynamics and their drivers? Are you creative and able to couple various data flows and integrated modelling
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more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world
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perturbation experiments to understand how cell type-specific epigenomes emerge during mammalian development, using gastruloids as an in vitro differentiation model. We aim for an open and collaborative work
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded