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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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characterization and fingerprinting. design and execute experiments to trap single proteins. perform in-depth data analysis and pattern recognition to extract protein properties from electrical current reads
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integrating single-molecule fluorescence detection and microfluidics Implementation of data acquisition and analysis software (programming) Methodological innovation and biological applications Who Should Apply
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generally be partitioned among 2-3 days of fieldwork and labwork and 2-3 days of data analysis. Fieldwork at Harvard Forest involves working full days (up to 8 hours) in year-round outdoor conditions. The
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genomic data analysis is desirable but not essential. - A strong interest in applications in biology and ability to work in a multidisciplinary team Additional Information Work Location(s) Number of offers
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integrating single-molecule fluorescence detection and microfluidics Implementation of data acquisition and analysis software (programming) Methodological innovation and biological applications Who Should Apply
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. A background in forest engineering, ecohydrology, and/or ecology would be ideal but is not required. Experience in numerical modelling, big data analysis, and plant ecological and physiological
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, and supportive atmosphere, equipped with state-of-the-art research facilities, including dedicated GPU clusters, data servers, and personal GPU-enabled workstations. You will join a multidisciplinary
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and Urology Faculty, is responsible for the independent conduct of a significant element of research projects. This includes assistance in study design, IRB submission, data analysis and grant
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: Hardware and embedded development: miniaturization of a multifunctional sensor (< 15 grams), real-time data transmission (Bluetooth/IoT), energy autonomy. Signal processing and sensor data analysis: analysis