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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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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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Are you interested in advancing our understanding of fracture and damage tolerance in fibre reinforced polymer composites, and in contributing to the development of new modelling approaches
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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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programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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to pharmacological intervention. We will combine studies in GPR6 knockout mice with pharmacological approaches in rodent models, including Flinders Sensitive Line (FSL) rats, a model of depression. By linking
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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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with sustainability assessment methods, including life cycle assessment and related modelling approaches, and you have applied these in cases and analysis related to biobased products and the bioeconomy