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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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methods tailored for different types of multivariate data, such as time series, spatial data, spatio-temporal data, functional data or tensor-valued observations. The work of the postdoctoral researcher
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the intersection of computer science and drug research, to support strategic focus on the use of AI in scientific research within the general area related to drug security. The position is at
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advancement of modern artificial intelligence (AI) methods in drug discovery and development. An ideal candidate will have strong background in machine learning, computational chemistry, or related fields, with
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offered a fully funded contract of up to 3 years. About the position The postdoctoral research position will require developing and applying cutting-edge machine learning methods to computer vision and
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Wellbeing Across Lifespan (SWAN) brings together expertise from the fields of medicine, life sciences, social sciences as well as computer and computational sciences to promote scientific and societal impact
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the research group of Professor Klaus Nordhausen in the project “Signal recovery in noisy spatial data”. The research group develops modern and efficient multivariate statistical methods tailored
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group, established in 2018 at the University of Oslo, has recently expanded to the University of Helsinki. The group specializes in developing computational methods to understand the regulatory mechanisms
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use a variety of molecular and cell biological methods together with bioinformatic approaches to evaluate the zoonotic potential of newly discovered henipa-like viruses in shrews. As a PhD student, you
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applications. Addressing food and nutritional security requires novel ways of producing sustainable, safe, affordable, healthy and flavourful food. Europe alone faces numerous challenges related to the rise in