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Field
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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. Experience with the use of large datasets. Strong skills in computer programming and computational statistics. Very good oral and written skills in English. Strong academic background documented with
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to pursue a scientific top position within or beyond academia. In addition to the activities in MAI, the project will benefit from a large machine learning research environment in the Norwegian Center
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machine learning is an advantage but is not required. Experience with the design and implementation of survey-experiments is an advantage but not a requirement. Alongside developing their own research ideas
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large and/or heterogeneous datasets, including quantitative and/or qualitative data Experience working with project partners and interdisciplinary research teams Required Education PhD in environmental
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chromosomes from scratch and control how they are inherited. The chromosome is the fundamental unit of inheritance and the only vehicle large enough to encode truly new biological functions. Yet we currently
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questions. Implements and adapts machine learning and AI-based approaches for high-dimensional epidemiological data, including variable selection, prediction modelling, and data integration. Retrieves
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position. Salary and Benefits: This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be
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benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With