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underrepresented in the field. What we look for Successful candidates should have previous experience in machine learning, statistics, artificial intelligence or in another relevant field, demonstrated by success in
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, Computer Science, Cognitive Science, Psychology or a related field excellent knowledge in at least one of these three key areas: quantitative User studies, statistical modelling of human experimental data
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-quality, scholarly wide research portfolio and scientific publication record in basic and applied ecology, and good methodological skills in modern field techniques and statistical methodology are essential
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The Institute for Molecular Medicine Finland (FIMM) at University of Helsinki | Finland | about 2 months ago
to develop statistical and machine learning models to predict disease occurrences. Qualification and requirements: The Data Science and Genetic Epidemiology Lab is looking for a data manager that will
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PhD position on Online Public Participation GIS (PPGIS) as a tool for university-city collaborations
) and statistical analysis skills. Previous knowledge in the 15 min cities -concept is an advantage. If you finish your master’s degree in the spring of 2024, you are also welcome to apply You have a keen
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) and statistical analysis skills. To reside in Finland while employed by the University of Helsinki. Mobility rule: researchers must not have resided or carried out their main activity (e.g., work
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statistical analyses. The selected candidates must have a Master's degree in musicology, music education, psychology, information science, or a similar subject by the time of commencement of the contract
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engagement in music through scale development and longitudinal and cross-sectional data analyses and must possess expertise in statistical methods and psychometrics. The postdoctoral researchers are expected
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. The positions focus on computational microbiome research. The applicants are expected to support the research group’s activities, develop and apply statistical, data science, and machine learning methods in
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Appreciated (but not mandatory) technical skills include SQL, Excel/Spreadsheets, Statistics and ML Basics, Programming (Python/R), Database Management, Data Warehousing, Visualization (at least some of those