12 machine-learning-"https:" "https:" "https:" positions at Nature Careers in Denmark
Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
-
Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
-
process systems engineering. The position aims to advance physically consistent and predictive thermodynamic modeling, including the integration of advanced machine learning methods, to support process and
-
analysis or habitat monitoring Highly valued: Experience applying AI or machine learning methods to remote sensing data Experience with drone-based point cloud collection Experience working with or advising
-
includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models
-
the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving
-
hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong
-
or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
-
are seeking a candidate for a vacant position as Tenure Track assistant professor in AI and machine learning to develop a novel research area within the use of agentic AI models for improved analyses of whole
-
, integrative systems biology, and machine learning. Our research is focused on analyses of data generated within the biological, biomedical, biotechnological and life sciences areas. The section has extended