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We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis. This is a unique opportunity to
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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responding to antibiotics. The project will investigate how complex interactions of the drug with the cell's physiology results in non-genetic variation in single-cell growth and gene expression, leading
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-leading group that brings together expertise across the clinical and basic science spectrum of the physiology and pathology of human movement and movement disorders. The Department incorporates groups from
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 months ago
of adipose tissue physiology and metabolic diseases (obesity and/or diabetes mellitus), will be valued; - Theoretical knowledge in human genetics, will be valued; - Fluency in written and spoken English
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repertoires across mice and other mammals, in part by generating new tools for genetic access to these cell-types for anatomical, physiological, and behavioral characterization. The position involves designing
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requirements: a) Applicants must hold, at the time of application, a Master’s degree in Biology, Agricultural Engineering, Biotechnology, Plant Physiology, Microbiology, Biophysics, Physics, Materials
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. Christian Lentz. Combining chemical biology, molecular biology, bacterial physiology and infection biology methods, our research is dedicated to unravel how bacterial pathogens functionally adapt
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the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes
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supply and biogeochemical cycling. Knowledge or experience of at sea observational and/or experimental work, or data analysis thereof, related to phytoplankton/microbial ecology/physiology and trace