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interest and solid foundational knowledge in at least one of the research projects Proven competence in computational design workflows, particularly in Rhino and Grasshopper Knowledge of Python, C#, finite
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research area: Python or C#, robotics, additive manufacturing, finite element analysis, or computational fluid dynamics. Experience in teaching and co-supervising thesis students at university level
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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processing & analysis (Python) We expect you to master the entire software development cycle, from analysis and design to programming, quality assurance, maintenance, documentation, and DevOps. We expect
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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(https://www.classique.aau.dk). CLASSIQUE will address a suite of fresh research challenges defined by the intersection of digital applications that have real-time requirements and quantum resources
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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, preferably with a background in behavioral neuroscience or signal processing (especially of bioacoustics data) - Programming experience (e.g. Python, R, Matlab, etc.) - Strong communication and
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and Memorial Sloan-Kettering Cancer Center, NY. Read more about the project here: https://health.medarbejdere.au.dk/en/display/artikel/supercomputer-and-ai-to-strengthen-danish-cancer-treatment-new
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background in robotics, autonomous systems, and/or control theory. The candidate should have good programming skills in Python and/or C++, and prior experience with robotics software frameworks such as ROS/ROS