Stanford University

Institution / Department Mohammed VI Polytechnic University Chemical & biochemical sciences.green process engineering Research Unit on Microbiome and Host-Pathogen Interactions Project Overview We are seeking a talented and motivated Postdoctoral Research Fellow to join our dynamic team investigating the role of microbiome dysbiosis in human health and disease. The project focuses on deciphering how imbalances in the gut microbiota contribute to chronic inflammatory conditions, colorectal cancer (CRC), and immune dysfunction, with an emphasis on discovering biomarkers and developing microbiome-based therapies. The research integrates multi-omics approaches (metagenomics, transcriptomics, proteomics, metabolomics) to understand how dysbiosis influences immune responses, barrier function, and host metabolism. Key Responsibilities Lead metagenomic, proteomics, and metabolomic profiling of clinical and experimental samples to identify dysbiosis signatures. Apply bioinformatics tools for microbiome data analysis (ex, QIIME2, MetaPhlAn, Kraken2). Collaborate on multi-omics data integration and analysis. Contribute to manuscript writing, conference presentations, and grant applications. Required Qualifications PhD in Microbiology, Immunology, Systems Biology, Bioinformatics, or a related discipline. Proven experience in microbiome research, particularly in gut microbiota. Experience with next-generation sequencing (NGS) and omics data analysis. Knowledge of microbial ecology, dysbiosis, and host-microbiome interactions. Familiarity with cell culture techniques. R, Python, or other data science tools for microbiome analysis. Publication record in peer-reviewed journals. Preferred Qualifications Experience with colorectal cancer models or inflammatory bowel disease (IBD). Familiarity with metabolomics (LC-MS, GC-MS) and analysis of microbial metabolites. Expertise in interkingdom microbiome research (fungi, viruses, archaea). Understanding of immunomodulation by the microbiota in cancer and chronic inflammation. Why Join Us? Work at the frontier of precision microbiome medicine and immune-oncology. Access to state-of-the-art facilities for genomics, proteomics, and metabolomics. Join an international, multidisciplinary team with collaborations across the US/Canada/Europe/Asia. Opportunity to lead high-impact publications and develop independent research projects. 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)

Département / Department :  Unité / Unit: Center for African Studies Université / University: Mohammed VI Polytechnic University  Intitulé de l’offre Postdoc / Title of the Postdoc offer: L’Afrique dans l’œuvre de Mokhtar Soussi Summary of the subject: One of the missions of the Center for African Studies is to document health and environmental issues. The candidate must have an interest in one or both of these fields, from an anthropological side. Health issues (infectious diseases) and environmental issues (biodiversity erosion) are to be documented. Responsibilities and tasks planned:  The work will focus on: Bibliographic review, Report and scientific publications. organizing workshop courses Skills required for the position: The candidate must have: PHD with skills in one of the following fields: history, philosophy, anthropology, sociology, psychology Rigor / motivation, Good communication skills, Teamwork An appropriate scientific background allowing him to deal with research questions, being able to mobilize the main approaches available in the field Sufficient scientific and methodological hindsight to understand the level of relevance of research approaches and to be able to combine them in an astute way in the analysis, definition, and resolution of project problems A minimum experience (professional or research) allowing him to move forward quickly and efficiently in a bibliographic analysis on a given theme and in the writing of scientific journals and articles.

Ref.: 533703 Work type: Full-time Department: Department of Data and Systems Engineering (14400) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff We are seeking highly motivated researchers to join our project on “Planning and Scheduling of Automated Material Handling Systems in Semiconductor Manufacturing Environments.” This project is carried out in collaboration with leading semiconductor companies and targets real-world, industrially relevant challenges. Our goal is to advance cutting-edge research while ensuring strong practical applicability. The research will concentrate on three interrelated areas:  a) Semiconductor Equipment Scheduling: In semiconductor fabs, a vast number of wafers are processed across hundreds or even thousands of manufacturing tools following highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times and lowering work-in-progress (WIP) inventory, thereby increasing throughput and overall manufacturing efficiency. b) Automated Material Handling System (AMHS) Scheduling: In modern semiconductor fabs, AMHS, typically realized through Overhead Hoist Transport (OHT), is responsible for transferring wafers between manufacturing tools. Given the massive production scale, the AMHS must handle tens of thousands of transports requests every day, ensuring timely and reliable delivery of wafers to the correct tools. Our research seeks to develop efficient and adaptive scheduling algorithms for AMHS systems to significantly reduce transport delays, improve material flow, and enhance coordination between logistics and manufacturing processes. c) Digital Twin System: We aim to construct a digital twin framework that integrates real-time data and simulation models to mirror the physical manufacturing and logistics systems. This enables performance monitoring, predictive analysis, and the evaluation of scheduling strategies in a virtual environment, thereby supporting more robust and adaptive decision-making in semiconductor manufacturing. Responsibilities:  a) To address the above challenges, applicants are expected to formulate mathematical models of the problems and develop efficient solution methods, particularly by leveraging techniques from machine learning and operations research. b) The applicants are expected to deliver research outcomes to our industry partners, to support practical applications in semiconductor manufacturing. c) The applicants are expected to write and submit high-quality academic papers. Qualifications a) Education: Ph.D. in Automation, Industrial Engineering, Systems Engineering, Computer Science, or a closely related field. b) Technical Skills: Strong programming proficiency is required. c) Research Experience: Relevant research experience in related problem domains, or research experience in scheduling, routing, and multi-agent pathfinding (MAPF) algorithms - Experience across multiple areas is a strong plus; Experience developing ML-based optimization approaches is a strong plus; A strong publication track record is highly desirable. d) Industry collaboration experience: Prior experience in collaborative R&D with industry partners is a strong plus. Application: Send your CV, a cover letter, and the contact information of three referees to Dr. Anbang Liu (anbang@hku.hk) and cc to Prof. Lin (shaoclin@hku.hk). The complete reference letters should be submitted as soon as possible after the application.