80 algorithm-development "https:" "Simons Foundation" Postdoctoral positions in Finland
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concerned with optimal transport for inverse problems. Optimal transport for inverse problems One of the central topics of the research projects is the further development of theory and methods
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at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
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-effectively predicting the rate of massively multicomponent organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning
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occupational health care and health insurance, sports facilities, and opportunities for professional development. University assists employees from abroad with their transition to work and life in Finland (https
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biology, multiomics and single cell methodology to drive projects focusing on modelling leukemia and immune cell dynamics with the goal to develop new personalised medicine approaches. As our new
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research group is associated with the newly established Center of Excellence in Neutron-Star Physics (https://neutronstars.fi ), providing us long-term funding, strong connections to related Finnish and
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pension fund, a generous holiday package, sports facilities, and opportunities for professional development (https://www.helsinki.fi/en/about-us/careers ). Required qualifications PhD (or near completion
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to the construction of the database, we offer an opportunity to conduct your own research on the project’s themes with an especial view to facilitating your career development. We offer the possibility to learn and
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of Languages and funded by an ERC Consolidator Grant awarded to Professor Tuomo Hiippala . The project develops novel methods and resources for studying multimodality, or how humans communicate using