23 data "https:" "https:" "https:" "https:" "Dr" "Goethe University" Postdoctoral positions at UNIVERSITY OF HELSINKI
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for separately (www.helsinki.fi/en/research/doctoral-education/the-application-process-in-a-nutshell ). The requirements for pursuing a doctoral degree at the University of Helsinki can be found at https
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development (https://www.helsinki.fi/en/about-us/careers ). How to apply A response to essential criteria (max 2 pages). Please ensure you provide demonstrated experiences from your previous work in relation
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Finland. More information here: https://www.helsinki.fi/en/about-us/careers/welcome-finland-information-arriving-staff How to apply The application must be submitted by 22 January. A round of interviews
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publications (free format but numbered to indicate the total sum of peer-reviewed articles) FURTHER INFORMATION Further information about the position and the research project may be obtained from Dr Elina Einiö
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knowledge, the goal is to elucidate bacterial genetic evolution that was shaped by human influence and make predictions to the future. The work provides the possibility to develop skills in microbiology, data
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opportunities for professional development (https://www.helsinki.fi/en/about-us/careers ). Application should include the following documents as a single pdf file: a cover letter, a CV, a publication list the
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provides support for internationally recruited employees with their transition to work and life in Finland. More information here: https://www.helsinki.fi/en/about-us/careers/welcome-finland-information
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Project: Statistical modelling the Evolution of Sex-Specific Differences in Life History and Immunity Supervisors: Dr. Elina Numminen, Faculty of Science, University of Helsinki, and Dr. Piret Avila
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10th, or until a suitable candidate is found. Further information For informal inquiries, please contact: Dr. Caio Graco-Roza University of Helsinki, Lammi Biological Station Email: caio.roza@helsinki.fi
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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules