-
computational and experimental approaches, leveraging the large-scale Microflora Danica dataset combined with samples taken from sites undergoing restoration. You will help conduct sampling, refine and apply
-
documented expertise in large-scale long-read metagenome projects within environmental genomics. This includes development of wet-lab protocols, sequencing, associated bioinformatics and usage of HPC SLURM
-
candidate must have documented expertise in large-scale high-performance computing analysis within environmental genomics and experience with systems administration of high-performance computing clusters
-
enable students, companies, and society at large to address the grand challenges in an increasingly volatile, uncertain, complex, and ambiguous (VUCA) world. The successful candidate will join a dynamic
-
-drive systems. Across the above areas, you are expected to contribute to model-based and data-driven/AI-based methods, including digital twins, physics-informed learning, data analytics, and AI-assisted
-
research and education directed towards the end-user. Your work tasks This position will involve working with real-time graphics, computer vision, applied AI and integrating Large Language Models (LLMs
-
more about the department at www.es.aau.dk. Your work tasks The PhD project is part of a bigger Novo Nordisk Foundation (NNF) New Exploratory Research and Discovery grant entitled: Information Theoretic
-
-support prototype focusing on environmental and social impacts Integrating knowledge on environmental, socio-economic, cumulative, and large-scale impacts to support decision-making Applying and testing
-
are in part funded by a DFF: Sapere Aude project (“Building TRUST in Text: Linguistically Motivated Language Model Detection”) and an NNF: Ascending Data Science Investigator project (“LM2-SEC