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design, development, and validation of material, control systems, and algorithms for next-generation soft haptic actuators and experiences. Note that the research involves significant interactions with
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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Alexandria, Virginia. The focus of these positions will be on quantum computing, quantum algorithms, quantum learning, quantum error correction, and quantum fault-tolerance. The successful candidate will join
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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researcher to join the Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. This exciting and ambitious research aims to develop new AI for shared human-AI decision-making in
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occupant harm from exposure to indoor bioaerosols. Key Responsibilities Responsibilities include, but are not limited to: Developing and analyzing new HVAC control algorithms to balance energy efficiency and
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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analysis, data modeling, and algorithm development. Experience with environmental analysis or microplastic research is a plus but not required. Strong analytical and problem-solving skills, ability
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includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related to applications and applied research
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Job description We are seeking two highly motivated postdoctoral researchers to join our research team based in the Van de Peer lab, under the supervision of Prof. Dr. Zhen Li, Assistant Professor