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Solid experience with statistical modeling, machine learning, or AI Practical skills in R and/or Python for data analysis and model development Familiarity with microbial ecology, genomics, or food safety
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scientific writing and communication skills very good knowledge of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in
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motivation to conduct interdisciplinary empirical research at the intersection of developmental psychology and cognitive neuroscience. You have experience with quantitative data analysis techniques such as
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, Biomedical Sciences, Molecular Sciences, Nanobiology). Experience with the basal transcription process, DNA damage response or with live cell imaging and microscopic data analysis is an advantage but not
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
Genetics, Neuroscience, Molecular Biology, or Related Discipline. Skilled in conventional molecular methods such as quantitative methods for qualitative and quantitative analysis of gene expression (qPCR
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psychology) or data analysis (e.g., data science, statistics) Affinity with data science (e.g., complex statistics, machine learning or computational modelling) or willingness to develop relevant skills (in
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-solving skills preferably skills in next generation sequencing-based methods and bioinformatics/computational data analysis Benefits: international working environment with communication in English and
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AI agents themselves. The candidate will explore behavioural analysis techniques. Another research questions is related to the definition and application of a unified policy through both legacy IT
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scenarios with only 200-300 primary users. Working Environment at CADIA You will join the Center for Analysis and Design of Intelligent Agents (CADIA) at Reykjavik University, one of Iceland's leading AI
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the