68 parallel-computing-numerical-methods positions at University of Southern Denmark in Denmark
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in ion transport and (2) using machine learning methods to design protein binders. The incoming postdoc will have the opportunity to mould the project to a significant degree. The candidate should have
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@iti.sdu.dk Conditions of employment The appointment as Associate Professor is permanent, while that as Assistant Professor is for an initial period of 4 years, part of a tenure-track programme. During
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). The successful candidate will contribute to the Nudge2Green research project, applying software development and AI methods to design digital nudging tools that promote sustainable consumer behavior in food choices
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the associate professorship is a permanent position. The positions will have employment at Campus Esbjerg and will also include occasional research- and educational tasks at our program at Campus Odense
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researchers to attract funding for their best ideas from the EU Framework Programme for Research and Innovation – ideas that can make a decisive impact on society and contribute to better health for all
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, Denmark’s famous fairytale author, the city is home to a vibrant and creative population that hosts numerous festivals and markets throughout the year. Application procedure Applicants are advised to read
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levels. In this project, the PhD student will learn to understand and apply modern causal inference techniques such as target trial emulation, marginal structural models and G-computation to observational
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emissions from agriculture to support the green transition. Protein chemistry, enzyme research, and screening of compounds against target proteins and bacteria. Upscaling of biochemical processes and methods
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their academic profile in LSP will be to work on so-called “zero programming” methods and tools to define a digital workflow from product design to production operations. Based on analyzing digital product
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Neural Networks (SSM-SNNs). The project includes the co-design and integration of a RISC-V processor for hybrid neuromorphic computing. The research aims to develop ultra-low-power computing chips