Management & Science University (MSU)

Job Title: Postdoctoral Researcher – AI/ML for Energy Systems Location: Ben Guerir Position Type: Postdoctoral Research Mohammed VI Polytechnic University is an institution dedicated to research and 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 of African development. A mechanism that enables it to consolidate Morocco's frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally. The Green Tech Institute at Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco, is seeking a highly motivated postdoctoral researcher to join our team in exploring the intersection of energy transition, circular economy, and sustainable construction production. This position aims to advance innovative solutions that promote sustainability in the built environment, focusing on the effective integration of renewable energy, resource efficiency, and waste reduction. The candidate must hold a PhD in Urban or Rural Development, Civil Engineering or related domain. The candidate is expected to have hands-on experience in field related to urban or rural planning, renewable energy and sustainable construction. Position Overview: We are seeking a talented and motivated Postdoctoral Researcher to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state-of-charge (SOC) and state-of-health (SOH) 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. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics for real-time battery health monitoring and fault detection. Collaborate with embedded systems and hardware engineering teams to integrate AI models into the BMS. Optimize AI/ML pipelines for resource-constrained environments, including edge AI applications. Guide PhD students and collaborate with engineers to implement advanced ideas. Author scientific publications, present findings at conferences, and contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and applying AI/ML models to energy systems or similar applications. Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on expertise in programming languages such as Python, R, or MATLAB. Solid understanding of battery systems, electrochemical processes, or energy management. Preferred Skills: Experience with time-series analysis, predictive modeling, and anomaly detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud) Understanding of BMS architecture and electric mobility systems.

Post Doctoral Fellowship: Development of a 'Battery Management System' for Lithium-Ion Batteries (11834) About UM6P : Mohammed VI Polytechnic University is an institution dedicated to research and 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 of African development. A mechanism that enables it to consolidate Morocco's frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally. About ACER CoE: The centre has been recently created to address enduring process challenges in Chemistry and Engineering disciplines and create an environment for interdisciplinary research. The research program of ACER is multidisciplinary, with faculty members from backgrounds in Chemistry, Chemical Engineering, and Environmental Engineering focusing on different research fields such as catalysis, separation, energy generation, conversion and storage, and organic optoelectronics intelligent and advanced polymers and materials. Project description: The Lithium-ion battery comprises multiple individual units known as "cells." Any deterioration or degradation in a single cell directly impacts the battery's overall performance and lifespan. Therefore, it is crucial to have a monitoring system in place for close oversight of this critical component. The battery management system (BMS) unit is not just a component, but a crucial element tasked with monitoring each cell of the battery and running algorithms to calculate state of charge (SoC), overall health, and more. For instance, in electric vehicles, the BMS carries out functions such as monitoring, controlling, optimizing, and ensuring safety to mitigate potential hazards related to battery performance. Its role is pivotal in the overall performance and safety of the vehicle, underscoring the importance of our work in this field. Various algorithms, models, and signals control different components of the BMS in lithium-ion batteries, including sensors, actuators, and controllers. In our facility, we are establishing a research unit focused on developing the necessary hardware and software components of a BMS to keep pace with the advancements in lithium-ion battery technology. Candidate Profile: Ph.D. in Electrical Engineering or related field. An in-depth expertise in batteries and renewable energy systems including fault detection, diagnosis, and performance improvement methods. Mastery of dynamic reconfiguration approaches. Mastery of power converters. Mastery of software tools including MATLAB, PSIM, Proteus, LabVIEW, SketchUp, SolidWorks, etc. Knowledge of microcontrollers, STM32, FPGAs, etc. Knowledge of communication protocols such as I2C, SPI, Profibus, Modbus, CAN, MQTT, and HTTP. Knowledge of the ROS environment. Undertake original research of international excellence. Engage in innovative international research of outstanding quality. Prepare papers for indexed journal publications, propose invention patents, and/or actively participate in sharing results at national and international conferences, workshops, and meetings. Communicating the development, progress, and results of research tasks to the research project team to identify the requirements for future activities. Develop collaborative links with the core scientific staff in related program areas to gain exposure and build knowledge on experimental/research activities and approaches and improve conceptual development and implementation. Participate actively in the drafting of research project proposals and the pursuit of funding opportunities. Supporting the purchase of appropriate equipment and managing relationships with international suppliers. Actively participate in supervising PhD students, guiding them through their research projects. Participate in national and international events related to the theme. Management of research projects. Candidature Submission: Applicants should submit: Cover letter outlining research experience and achievements and stating research interests. Curriculum Vitae with a list of publications. Three references who are not UM6P faculty. One reference letter UM6P.

Institution/Department Mohammed VI Polytechnic University Chemical & biochemical sciences.green process engineering Research Unit on Microbiome and Host-Pathogen Interactions Project Overview: We are looking for a highly motivated Postdoctoral Research Fellow to join our interdisciplinary team focused on antimicrobial resistance (AMR). The selected candidate will have a vital role in an innovative project that aims to map the resistome and clarify the mechanisms of multidrug resistance across diverse microbiomes—comprising clinical, environmental, and host-associated microbial communities. This project seeks to comprehend how antimicrobial resistance genes (ARGs) disseminate within microbial populations via horizontal gene transfer (HGT) and mobile genetic elements (MGEs) and how these processes affect human health, particularly regarding colorectal cancer (CRC). Key Responsibilities: Perform shotgun metagenomics and whole-genome sequencing (WGS) on microbial samples from various environments (clinical, environmental, tumor-associated microbiomes). Develop and implement bioinformatics pipelines for resistome, mobilome, and virulome profiling using tools such as MEGARes, CARD, VFDB, and PlasmidFinder. Investigate horizontal gene transfer (HGT) dynamics and plasmid-mediated dissemination of ARGs across microbial communities. Conduct phylogenetic and comparative genomic analyses to uncover the evolution of multidrug resistance in pathogenic bacteria. Analyze co-occurrence networks between resistance genes, virulence factors, and mobile elements in microbiome datasets. Collaborate with clinical partners and microbiome researchers to integrate multi-omics data for comprehensive resistome analysis. Publish high-quality research articles and present findings at international conferences. Contribute to grant writing and development of new research proposals. Required Qualifications: PhD in Microbial Genomics, Bioinformatics, Molecular Microbiology, Infectious Disease Biology, or a related field. Proven experience with high-throughput sequencing technologies (Illumina, Nanopore) and metagenomic analyses. Strong background in bioinformatics tools for microbiome analysis (QIIME2, Kraken2, MetaPhlAn) and AMR gene identification (MEGARes, CARD, ResFinder). Proficiency in Python, R, or Perl, with experience in Linux/Unix environments. Solid understanding of antimicrobial resistance mechanisms, horizontal gene transfer, and mobile genetic elements. Evidence of scientific publications in peer-reviewed journals. Excellent communication and teamwork skills. Preferred Qualifications: Experience in clinical microbiome research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning approaches for resistome prediction or biomarker discovery is a plus. Why Join Us? Access to cutting-edge technologies (mass spectrometry, next-gen sequencing, high-performance computing). Work on high-impact research addressing one of the urgent challenges in global health—antimicrobial resistance. Collaborate with a multidisciplinary team of microbiologists, bioinformaticians, clinicians, and data scientists. Opportunity to lead high-profile publications and contribute to international consortia. Career development support, including grant writing, conference funding, and training opportunities. Application Process: Applicants should submit the following in a single PDF file: A Cover Letter explaining their interest and fit for the position A detailed Curriculum Vitae (CV) Names and contact details of 2–3 references Up to three key publications (optional)