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and techniques (e.g. isotopic and spectroscopic techniques) that would allow him/her to track and determine the origin, the fate and speciation of elements from the parent material and underground water
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developing robust and implementable monitoring, reporting, and verification (MRV) systems to allow us to track the impact of agricultural practices on organic carbon sequestration in the soils and emissions
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observation, and deep-space astrophysics. Key qualifications: PhD in Physics, Electrical Engineering, or related field Proven experience in cryogenic detectors and low-noise electronics Track record in space
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. The main objective of the project is to study the interaction between machine learning and wireless communication fields. The successful candidate will answer questions such as how to assign limited
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monitoring and electric vehicle battery tracking. Integrate environmental and energy sensors with real-time data collection and analysis systems. Deploy prototypes in the field and optimize their performance
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Green Process Engineering Department (CBS) is a component of the Mohammed VI Polytechnic University (UM6P). The main objective of CBS is to set up a distinctive research-teaching program, of international
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. The main objective of CBS is to set up a distinctive research-teaching program of international level, in order to meet the research and teaching challenges of UM6P, in particular on green and environmental
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data into actionable insights for research and decision-making. Experience working in multidisciplinary teams. Track record of high-level scientific publications and presentations at international
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experts. Track record of publishing in high-impact journals and presenting research at international conferences. Commitment to research excellence. Interest in addressing African development challenges
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
classifiers). Proficiency in programming languages such as Python, R, and experience with bioinformatics pipelines. A proven track record of scientific publications in metabolomics, AI, or computational biology