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globally and creates conditions for the emergence of innovations. We are now looking for Postdoctoral researcher in applied quantum computing in material science and modelling (1.8.2025-31.7.2028) to join us
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the "Mercury in the solar wind" ERC project at the Finnish Meteorological Institute. The postdoc will apply our global particle-based models to study the solar wind influence on Mercury and its environment and
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author) in the field of computational biophysics (molecular dynamics simulations and/or quantum chemistry). Any experience in development and application of AI/ML methods in tandem with modeling and
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to: Develop and apply machine learning models for analyzing complex datasets related to nature conservation. Establish and maintain code and data repositories to ensure efficient workflow and collaboration
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than 14 March 2025. Position and salary We are seeking to recruit a Postdoctoral Researcher to join an interdisciplinary project focused on aquatic ecosystem services, hydrological modelling, and nature
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integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal regulatory interactions, (ii) modeling networks based on single-cell and spatial omics data, and (iii
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-morbidities; life-course models and pathways' your responsibilities will include developing genome-wide prediction of human growth models Assisting the existing team in developing new methods to model human
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-requisite for the position. Previous experience of working with in vivo models of cancer is considered an advantage. Strong command in written and spoken English is required. The chosen applicant is expected
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can be found below: Antti Honkela (UH) differential privacy; privacy attacks; foundation models both Postdoctoral and Doctoral Researcher Samuel Kaski (Aalto) Probabilistic Machine Learning; automatic
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found below: Recruiter Research Group Research Interests Postdoc and/or Doctoral researcher Antti Honkela (UH) Trustworthy Machine Learning differential privacy; privacy attacks; foundation models both