Universite Pierre Mendes France - Grenoble 2

About Mohammed VI Polytechnic University (UM6P) Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and Africa. UM6P is an institution oriented towards applied research and innovation. On a specific focus on Africa, UM6P aims to position these fields as the forefront and become a university of international standing. More than just a traditional academic institution, UM6P is a platform for experimentation and a pool of opportunities, for students, professors, and staff. It offers a high-quality living and study environment thanks to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. In its research approach, the UM6P promotes transdisciplinary, entrepreneurship spirit and 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 critical mass. Thus, academic liberty is promoted as far as funding is developed by research teams. The research programs are integrated from long-term research to short-term applications in linkage with incubation and start-up ecosystems. About the Chemical & Biochemical Sciences Green Process Engineering (CBS) The Chemical & Biochemical Sciences Green Process Engineering Department (CBS) is a component of the Mohammed VI Polytechnic University (UM6P). The main objective of CBS is to set up a distinctive research-teaching program, of international level, to meet the research and teaching challenges of UM6P, on green and environmental chemistry applied to all aspects of chemical sciences: organic and inorganic chemistry, analytical chemistry, chemical biology, biochemical and thermal reactions. Research at CBS is organized around several major areas, which aim to answer challenging industrial questions, from complex chemical and biochemical reactions to scale-up and validation of process engineering. CBS projects aim at an in-depth understanding of the molecular mechanisms of all transformations to propose new original alternatives in terms of efficiency, environmental friendliness, and sustainability. Job Description We are seeking a postdoctoral researcher to work on innovative solutions in desalination and sustainable water resource management, with a particular focus on assessing the quality of water intended for agricultural use. The selected candidate will contribute to the development and optimization of desalination processes (membrane-RO), the analysis of treated water quality (especially in relation to agronomic requirements), and the study of environmental impacts associated with the reuse of such water. Key Responsibilities: The postdoctoral researcher will be responsible for developing and optimizing desalination processes, particularly reverse osmosis, with a focus on sustainability and efficiency. The work will involve improving the performance of treatment systems and proposing solutions tailored to agricultural water needs. A key part of the role will be to assess the quality of desalinated water in relation to agronomic requirements and to study the potential environmental impacts of its reuse, particularly regarding soil salinity and contamination of water resources. The researcher will collaborate with multidisciplinary teams, take part in testing campaigns (in the lab or in the field), analyze the collected data, and contribute to the dissemination of results through scientific publications, technical reports, and participation in innovative projects. Candidate Criteria PhD degree in Chemistry, with a specialization in inorganic chemistry, water treatment, or a closely related field, is required. Proven experience integrating water-related challenges within the agricultural context is highly desirable. Research Excellence: A strong research track record focused on desalination, water treatment, or sustainable processes, with direct or potential applications in the agricultural sector, demonstrated through publications in reputable international scientific journals. Collaborative Mindset: Proven ability to collaborate effectively with interdisciplinary teams and external partners to address complex challenges. Communication Skills: Excellent communication and presentation skills in English. Proficiency in French is a plus. Entrepreneurial Spirit: Alignment with UM6P's focus on entrepreneurship, Application and Selection: The application folder must contain: Detailed CV, Cover letter along with a comprehensive presentation of the candidate background, research work, projects, and key activities (publications and achievements) Research and teaching statement, entrepreneurial ideas, and concepts if any, and services to UM6P community: max 3-4 pages, 3 reference letters. Our Offer Very competitive salary and benefits package. A unique set of research partners and collaborators.

The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research. We are ambitious and have a bold vision - shaping ourselves into one of the best universities in the world - which we are achieving through the talents and endeavour of every employee. Our high-achieving Advancement team recently closed its first global campaign, and is now building on this success to drive even greater philanthropic impact. Our high-achieving Advancement team recently closed its first global fundraising campaign, and is now building on this success to drive even greater philanthropic impact. The Advancement team of 25 ambitious professionals work with our global community of 153,000 alumni in 185 countries delivering alumni engagement activities and securing donations to support research and students at the University. The role We are seeking an outstanding assistant to provide high-quality, professional administrative and PA support to the Director of Advancement and the Advancement Leadership Team. This is a key role for an organised, proactive and personable individual who takes pride in delivering a seamless service, enabling senior leaders to operate effectively and efficiently within an ambitious Advancement function. The University operates a hybrid working approach and this role will be a minimum of three days per week office-based with flexibility to attend campus more frequently when required. Part-time hours will be considered for the right candidate. About you If you are highly efficient, dependable and trustworthy, with excellent administrative skills and a naturally warm and professional manner, we would welcome your application. You will join a friendly and forward-looking team at the University of Surrey, working in a collaborative environment and contributing to work that directly supports students, research and the University’s global ambitions.  How to apply To apply, please upload a CV and cover letter outlining why you would be a suitable candidate for the role. If you would like to discuss the role further, please contact Amintha Buckland, Associate Director, Philanthropy - a.buckland@surrey.ac.uk for an informal chat. Further details Job Description

Position Overview: We are seeking an outstanding Postdoctoral Researcher in Artificial Intelligence (AI) and Data Science with expertise in multi-omics data integration for health and precision medicine. The successful candidate will join a multidisciplinary team developing AI-driven approaches to integrate and analyze genomics, transcriptomics, proteomics, metabolomics, and microbiome datasets to uncover biomarkers, therapeutic targets, and mechanistic insights into complex diseases. The project addresses critical challenges in personalized medicine, disease stratification, and multi-modal data fusion, enabling next-generation solutions in precision health and biomedical research. Scientific Challenges Addressed in the Position: Heterogeneity and high dimensionality of multi-omics data requiring advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning for comprehensive systems biology modeling. Identification of causal relationships and biomarker discovery through integrative approaches. Time-series and longitudinal multi-omics data analysis for disease progression modeling. Explainability and interpretability of AI models to support clinical decision-making and regulatory compliance in healthcare settings. Scalability and computational efficiency in processing and integrating massive multi-omics datasets from clinical cohorts. Key Responsibilities: Design and implement AI/ML pipelines for multi-omics data integration, including supervised and unsupervised learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view learning, transfer learning, and data fusion techniques to integrate heterogeneous omics datasets and clinical metadata. Conduct network-based analysis (gene regulatory networks, protein-protein interaction networks, metabolic networks) to identify key disease drivers and biomarkers. Build predictive models for disease classification, patient stratification, and treatment response prediction. Collaborate with biologists, clinicians, and bioinformaticians for data interpretation and validation of computational findings in clinical or experimental settings. Disseminate research outcomes through publications in high-impact journals, conference presentations, and workshops. Mentor and support the training of graduate students and early-career researchers in AI and multi-omics integration. Required Qualifications: Ph.D. in Bioinformatics, Computational Biology, Data Science, Artificial Intelligence, or a related field. Proven experience in multi-omics data integration, omics data analysis (genomics, transcriptomics, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases (e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal modeling, and graph-based AI approaches. Experience in multi-modal data fusion, representation learning, and heterogeneous data integration. Strong publication record in relevant peer-reviewed journals. Excellent communication skills and ability to work in a multidisciplinary environment. Familiarity with cloud-based computing platforms (AWS, Azure, Google Cloud) and high-performance computing (HPC) environments. Understanding of data privacy, security, and ethical considerations in handling clinical data. Application Process: Interested candidates should submit the following documents in a single PDF: A cover letter outlining their research interests, motivation, and relevant experience. A detailed Curriculum Vitae (CV) with a list of publications. Contact details of two academic referees.