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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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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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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
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clinical sample collections and pre-clinical models that more comprehensively capture the cellular and molecular heterogeneity of this multi-focal cancer. Your job responsibilities As Postdoc in prostate
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biophysics, with demonstrated expertise in at least one of: protein X-ray crystallography (including data collection, structure solution, and model refinement), cryo-EM, or NMR spectroscopy. Strong background
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modelling Experience with hardware-in-the-loop (HIL) emulators such as dSPACE, OPAL-RT, and Speedgoat Experience in power systems and system optimization Knowledge of battery storage technologies and battery
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with proteomics experts. You will be working primarily with mice models and primary neuron cultures. You will be involved in the Center for Proteins in Memory (PROMEMO) funded by the Danish National Research
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behaviour change theory (e.g. COM-B, the Theory of Planned Behaviour, or the Value-Belief-Norm model) as applied to sustainability or circular economy contexts. Experience with citizen science, co-creation