76 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions at UNIVERSITY OF HELSINKI
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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-arriving-staff
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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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direction and advancement of life science research infrastructures across Finland. About Biocenter Finland Biocenter Finland (BF, https://biocenter.fi ) is a national organization, which develops and
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development (https://www.helsinki.fi/en/about-us/careers ). Required qualifications PhD (or near completion) in evolutionary biology, ecology, genetics, or related fields. Expertise in molecular genetics
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applied questions such as environmental management and risk assessment. For more information on EnvStat, please see https://www.helsinki.fi/en/researchgroups/environmental-and-ecological-statistics A
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candidate will work with Prof. Antti Kupiainen on problems of interest to the Simons Collaboration on Probabilistic Paths to Quantum Field Theory https://probabilistic-qft.org/ . We welcome applications
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. The suitable candidate has computer literacy (Windows, Excel, Word) and an ability to work as a part of a team and positive attitude. The required language proficiency for this position is Finnish and
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. Experience with machine learning or deep learning-based segmentation algorithms. Experience with statistical analysis to interpret quantitative image data and generate biological insights. Experience in
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-in-a-nutshell ). The requirements for pursuing a doctoral degree at the University of Helsinki can be found at https://www.helsinki.fi/en/research/doctoral-education/eligibility-and-educational
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of living together, in this position with reference to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning