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). Experience in numerical modeling and data analysis. An interest in groundwater contamination, risk assessment, and sustainability. Programming experience (Python, MATLAB, or similar) is desirable but not
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aligned nations may face considerable challenges. How to apply For further information please contact: Name: Enric Grustan-Gutiérrez Email: e.grustan@cranfield.ac.uk If you are
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implement a combination of metagenomic sequencing techniques to comprehensively characterise baseline levels of microbial pathogens in wastewater and surface water and compare our findings with data
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PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded. Further information on the lab: https://www.pdn.cam.ac.uk/directory/ewa
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. Further details are available on the International website . Funding information: The studentship is for 3 years and provides a tax-free stipend of £20,780 per annum for the duration of the studentship plus
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, lack of transparency, safety assurance, and sustainability. You will work at the forefront of AI research, exploring formal and dynamic verification methods, explainable AI, and data space integration
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or online meetings as needed. All the supervisors are experienced in data analysis and Python programming. Feasibility: The project will mainly require using the outputs of an ocean state estimate to compute
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degree in Electrical Engineering, Biomedical Engineering, Mechanical Engineering, or a related field, with a genuine interest in Wearable Technology, Sensor Development, Biomedical Devices, and Data
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health measurement kit, under 1-2-1 supervision. These tasks will include the collection of data on photosynthetic activity seedlings within a woodland plantation site, utilizing a chlorophyll meter
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hardware and data handling toolchains. The research will also involve modelling, analysis and characterisation of the system and components. The PhD will include a placement of minimum 3 months with Team