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the position as soon as possible: Scientist (m/f/d) The successful candidate will conduct the economic analysis of the impacts of modern site-specific sensor and application systems for fertilization in
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/algorithmic modelling. Experience with multidisciplinary IoT systems, including low‑power sensor networks and power‑constrained device architectures. Hands‑on experience with experimental testing in
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and Gera in Lesvos Island, including assessments of survival, growth, and environmental conditions using in-situ measurements and continuous sensor data. The researcher will also support the
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related fields Expert knowledge of building air-conditioning and mechanical ventilation, simulation, building automation and control, sensor network, thermal energy storage, indoor air quality, heat
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Apply and key information This project is funded by: Department for the Economy (DfE) Summary The transition to net zero presents both an opportunity and a challenge for Northern Ireland’s housing
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: Support the implementation and maintenance of field sites monitoring GHG emissions and water fluxes using automated chamber systems and IoT sensor networks. Assist in the calibration, deployment, and
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for robotics, electrical and digital control systems, sensors and sensor networks within the Advanced Manufacturing specialisation through the UTAS Virtual Learning Environment (VLE) Foster student success and
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Entitlement: 33 days annual leave, plus 9 buildings closed days for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value
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-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus
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Supervisor: Tenured Associate Professor Serkan Turkmen, Estonian Maritime Academy: Estonian Maritime Academy: Green Maritime Technology Research Group Proposed Thesis: Towards net zero in Maritime Industry