111 software-engineering-model-driven-engineering-phd-position Postdoctoral research jobs in Morocco
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innovation in Africa and aims to position itself among world-renowned universities in its fields. The University is engaged in economic and human development and puts research and innovation at the forefront
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geological engineering, or a PhD in a related field with mining/mineral processing experience. Knowledge of process mineralogy, froth flotation through past research, coursework, or job experience. Proficiency
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Post-doc position: Engineering thin film materials and structures via physical vapor deposition for energy applications About Mohammed VI polytechnic University (UM6P) Located at the heart of the
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research with real-world impact. Qualifications and Skills are: PhD degree in Chemistry, Materials Sciences or a related engineering field. Proven experience in nano/micro-material synthesis. Good knowledge
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Position Overview: We are seeking a highly motivated Postdoctoral Researcher to join our interdisciplinary team focused on Artificial Intelligence (AI)-driven retrosynthesis and reaction prediction
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downconversion layer Analysis of data using software tools such as MATLAB, Python, or Origin. The candidate must be familiar with materials studio software and any other materials modeling software. Experience in
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. Required Qualifications : Doctorate: A PhD in Industrial Engineering, Environmental Engineering, Waste Management, Data Science, or a related field. Modeling Expertise: Proven experience in designing
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between catalysts and reactants. Write scientific reports and research articles and participate in conferences. Candidate Profile PhD degree in Chemical Engineering, Materials Science, or a related field
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sustainable formulations for different applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of formulation chemistry to develop promising solutions and
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of software tools for the broader research community. Responsibilities: Develop and implement transformer-based genomic language models for bacterial genome analysis. Train and evaluate models on large-scale