Sort by
Refine Your Search
-
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
-
of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
-
The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
-
: Overcoming Inequity in Embodied Learning in Danish Vocational Education and Beyond, funded by Independent Research Fund Denmark. This is a full-time (37 hours per week), fixed-term (24 months) postdoctoral
-
others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent frameworks). Hands-on experience with data representation and embeddings, ideally applied
-
. In a diverse and international research environment, dedicated employees are looking to generate new knowledge within biomedical research areas such as infection and inflammation, membranes
-
to Associate Professor Anne M. Landau. Your competences You have academic qualifications at PhD level in neuroscience, pharmacology, biomedical science or a related discipline. You have experience in
-
groundbreaking research. In a diverse and international research environment, dedicated employees are looking to generate new knowledge within biomedical research areas such as infection and inflammation
-
-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
-
data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus