15 postdoctoral-machine-learning Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY in Morocco
Sort by
Refine Your Search
-
) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
-
. The primary objective is to design robust and efficient planning solutions—integrated within a digital twin—that account for the uncertainties and variability inherent in industrial processes. Machine learning
-
in Operations Research. Strong skills in Machine Learning. Practical experience in mining or industrial environments (through projects, thesis, or postdoctoral work). Ability to work effectively in a
-
recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
-
. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic analysis, facilitating the discovery of efficient and sustainable synthetic routes for complex
-
, emissions, and productivity. Decision-Support & MCDA Implement a machine-learning-driven multi-criteria decision analysis to rank and select optimal decarbonization pathways. Collaborate with industry and
-
Titre: ASARI - Postdoctoral Position in Quantum dots/nanomaterials/Photovoltaics/Solar Energy Entity: Water and Energy department, ASARI. About UM6P: Mohammed VI Polytechnic University (UM6P) is an
-
(especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning, particularly for multi-variable simulations. Knowledge of complex systems
-
interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical
-
, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases