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development section, specifically: Develop and maintain custom Python graphical user interfaces that enhance the usability of the group’s research tools. Optimize data workflows through efficient data
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communication. Strong competences in mathematical modelling and simulation of flow, heat transfer and dynamic system behaviour, including use of tools such as MATLAB/Python and CFD. Strong hands-on experience
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, including signal processing, optimization, machine learning or information theory; Experience in programming, e.g., in C++, Python or Matlab. Qualification requirements PhD stipends are allocated
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program across Aalborg and Copenhagen campi. This includes delivering courses in teaching programming e.g. C# and Python, real-time graphics rendering, use of generative AI as well as AI application
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Assistant professor position (non-tenured) in molecular dynamics simulations of plant hormone tra...
candidate has A relevant Ph.D. degree and a documented background in molecular biology and biochemistry. Experience in performing and analysing molecular dynamics simulations. Proficiency in Python
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Ph.D. degree and a documented background in molecular biology and biochemistry. Experience in performing and analysing molecular dynamics simulations. Proficiency in Python or comparable programming
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of tools such as R, Python, GIS, Git or similar data-science software. Solid experience with community data and biodiversity monitoring. A broad ecological background, ideally including plants and
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characteristics: be self-motivated, having a can-do attitude, willing to learn be able to program in C plusplus; ; and/or Python be at least familiar with ROS2 and Linux have decent understanding of robotics
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to damage detection, condition monitoring, and forecasting. You are proficient in Linux and Python, preferably with experience in PyTorch or a similar deep learning framework, and you are able to design and
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Programming in Python, R, SQL, Java, or similar languages Spatial and spatiotemporal methods when relevant, including geo-visualization, spatial optimization, and spatially explicit modelling for sustainability