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in Africa. Main responsibilities: The selected candidate will be expected to: Collect the data regarding the production of targeted crops in Africa, work with the project team and valorize data as
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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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collaboration with external institutions for developing up to date science and at continent level in order to address real challenges. All our programs run as start-ups and can be self-organized when they reach a
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for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools (e.g., PyTorch/TensorFlow, rasterio/GDAL). Ability to work independently and produce reproducible
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scientists with a strong background in thermal sciences, energy systems, or water technologies, and a demonstrated ability to operate in research environments oriented toward sustainability and impact. The
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, seminars and other national and international events related to machine learning. work effectively with the DMG team and help nurture internal and external collaborations with academic and industrial
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to the supervision of Ph.D. students and guide their research work Candidate Profile: Due to the multidisciplinary character of ACER CoE, the ideal candidate must have as well a multidisciplinary scientific profile
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or secondary ores. The work will include the study of the thermal and physicochemical properties of minerals, design and execution of thermal treatment experiments (e.g., calcination, roasting, smelting), and
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technologies and mineral beneficiation processes. Strong analytical and problem-solving skills. Excellent written and oral communication skills in English or French. Ability to work independently and as part of
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seminars. Interdisciplinary collaboration: Work closely with a multidisciplinary team of scientists, agronomists, and environmental specialists to develop integrated soil fertility management systems