Georgetown University - McDonough School of Business

About Mohammed VI Polytechnic University (UM6P): Located at the heart of the Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with an international standard, was established to serve Morocco and the African continent and to advance applied research and innovation. This unique university, with state-of-the-art infrastructure, has woven an extensive academic and research network, and its recruitment process is seeking outstanding academics and professionals to promote Morocco and Africa’s innovation ecosystem. About the department Vanguard works on the development of innovative and interdisciplinary applied research projects. From technological innovation to the transfer of research to industry, Vanguard has also the mission of developing an ecosystem of related start-ups. For more information about our Center, please visit our webpage: https://vanguard.um6p.ma/ Offer description: There are many systems of interest to scientists that are composed of individual parts or components linked together in some way. Examples include the Internet, a collection of computers linked by data connections, human societies, which are collections of people linked by acquaintance or social interaction, transportation systems and biological interactions. These systems are represented as networks. A network is a set of objects that are connected to each other in some fashion. Mathematically, a network is represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the edges represent relationships between objects. A common way to represent a graph is to use the adjacency matrix associated with the graph. However, adjacency matrices only model networks with one kind of objects or relations between the objects. Many real world networks have a multidimensional nature such as networks that contain multiple connections. For instance, transport networks in a country when considering different means of transportation. The train and bus routes are different types of connections and should in some models be represented by different kinds of edges. These kind of situations can be modeled using multilayer networks which emphasize the different kind or levels, known as layers, of connections between the elements of the network and the interactions between these levels as well. In order to capture the structure and complexity of relationships between the nodes of networks with a mul-tidimensional nature, tensors are used to represent these kind of networks. For example, the transport network mentioned earlier would be represented by a 4th order tensor A 2RN_L_N_L  where L is the number of the layers (transportation means) and N is the number of nodes (stations or stops). Using convenient tensor products, the goal is to define measures to analyze different multidimensional networks based on their adjacency tensors. However, collecting all the interactions in the systems and sometimes even observing all the components is a challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non fully observed data. These methods can be applied to complete or predict links in a network. However, missing information in a network can include both missing edges and nodes which makes classical matrix completion method insufficient. However,we may collect other information and features about the elements of the network. Therefore, side information about the nodes along with the observed edges need to be exploited. The problem of network completion arrises also for applications where the network has a multidimensional representation such as multiplexes and multilayer networks. Since multidimensional networks can be represented by tensors, one can think of applying tensor completion methods which have proved to be efficient in many applications such as image and video reconstruction. However, the same issue arises, tensor completion methods can not be directly applied to recover the links of the network giving the fact that the data is sparse most of the time. We aim to use auxiliary information about the multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor minimization and tensor decompositions paired with auxiliary information in order to recover missing links in a multilayer network with connected components. An important constraint in network completion is that the factorization must only capture the non zero entries of the tensor. The remaining entries are treated as missing values, not actual zeros as is often the case in sparse tensor and matrix operations. Therefore, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing multidimensional networks by studying the theoretical foundations behind randomized algorithms in the context of sparse optimization and applications in real world data sets. We are also interested in exploring opportunities for  parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel algorithms and methodologies for tensor completion in multidimensional networks. This includes exploring optimization techniques, tensor decompositions, and incorporating auxiliary information for more accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing efficient and scalable algorithms that can handle large-scale datasets. Tensor Analysis: Analyze the structure and properties of multidimensional networks represented as tensors. Investigate different measures and metrics for characterizing network connectivity and relationships. Sparse Optimization: Address the challenge of sparse optimization for tensors by integrating randomized algorithms into optimization frameworks. Study the theoretical foundations of randomized algorithms in the context of sparse tensor operations and apply them to real-world datasets. Parallel Computing: Explore opportunities for parallelism in the tensor completion process to enhance computational efficiency. Investigate parallel algorithms and architectures that can exploit the inherent parallelism in tensor operations. Collaboration: Collaborate with interdisciplinary teams including computer scientists, statisticians, and domain experts to apply tensor completion techniques to real-world applications, especially in the case of social sciences. This involves effective communication and coordination to ensure the successful integration of mathematical methods into practical systems. Publication and Dissemination: Publish research findings in top-tier journals and present results at conferences and workshops. Disseminate knowledge and contribute to the academic community by sharing insights and methodologies developed during the course of the project. Mentorship and Training: Provide mentorship and guidance to graduate students and junior researchers involved in related projects. Share expertise and knowledge in applied mathematics, tensor analysis, and network science to foster the professional development of team members. Qualifications and experience essential PhD in Applied Mathematics in the fields of Numerical Linear Algebra, or equivalent. Prior experience on the subject is highly desired.

Département / Department:  Unité / Unit : Center for African Studies Université / University : Mohammed VI Polytechnic University  About UM6P: Mohammed VI Polytechnic University (UM6P) is a forward-looking, internationally oriented institution of higher education dedicated to excellence in teaching, research, and innovation. Its mission is firmly anchored in supporting the sustainable economic development of Morocco and the African continent. UM6P places applied research and technological innovation at the core of its academic model, with the ambition of positioning Africa-driven research at the global forefront and establishing itself as a university of international standing. Beyond the traditional role of a university, UM6P serves as a dynamic platform for experimentation, innovation, and impact. It offers a high-quality academic and living environment, supported by state-of-the-art infrastructure, cutting-edge laboratories, and a vibrant research ecosystem that empowers students, faculty, and staff to fully realize their potential. UM6P’s research philosophy is grounded in transdisciplinarity, entrepreneurship, and strong collaboration with external partners, including industry, public institutions, and international research organizations. This approach enables the development of advanced, solution-oriented science capable of addressing real-world challenges at both national and continental scales. All academic and research programs at UM6P are conceived and managed with a start-up mindset, fostering agility, autonomy, and impact. Programs are encouraged to self-organize and scale once they reach critical mass, with academic freedom strongly supported through research-driven funding models led by the teams themselves. Résumé du sujet / Summary of the subject: The candidate submits a proposal on global health, public health in Africa, and history of medicine. On the continent, chronic diseases are becoming a major concern. The research will document this development and examine what measures are being taken to remedy this problem. More generally, one of the main issues is the link between chronic diseases and public health. What makes the notion of public health expand to become global health? This topic is in line with one of the orientations of the Center for African Studies: health. The candidate will collaborate with the Medical School. He /She has to be able to teach in English medical ethics. Responsabilités et taches prévues / Responsibilities and tasks planned:  The work will focus on: Bibliographic review, Report and scientific publications. organizing workshop courses Compétences requises et exigence du poste / 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.

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. Mohammed VI Polytechnic University The Chemical & Biochemical Sciences department (CBS). Job Title: Postdoctoral positions Job description: The Chemical & Biochemical Sciences department (CBS) at Mohammed VI Polytechnic University is currently offering an opportunity for a full-time Postdoc in the field of applied microbiology and Bioprocess. We are currently looking for highly motivated candidates with a strong background in biochemistry, bioprocessing, and applied microbiology. Additionally, candidates should be knowledgeable in molecular biology and chemical analysis. Proficiency in biostatistics is very desirable. The postdoctoral fellow will play an integral role within our dynamic, multidisciplinary team dedicated to waste valorization and the production of high-value compounds. To qualify for this position, candidates should have a Ph.D degree in a related discipline, and a track record of publications in peer-reviewed journals. The selected candidate will work closely with our team of researchers, doctoral and master's students, as well as technicians, contributing to cutting-edge research in our department. Main Responsibilities: The Postdoctoral Fellows will collaborate with the research team to plan, execute, and analyze research activities and experiments, therefore, contributing to the advancement of knowledge in their field. They will prepare detailed technical reports summarizing techniques and methodologies, results, and conclusions. Additionally, they will mentor and supervise both graduate and undergraduate students, aiding in their academic and research progress. Furthermore, they will publish research findings in high-impact peer-reviewed journals, sharing knowledge to the global scientific community. Criteria of the candidate: To be considered for this position, candidates should meet the following criteria: Recent PhD: Hold a Ph.D. earned within the last five years in Microbiology, Bioprocess, Environmental Biotechnology, or a related field, demonstrating a commitment to cutting-edge research. Expertise: Possess a strong academic background in applied microbiology, Phycology, and Biochemistry, highlighting your knowledge and skills in these disciplines. Analytical Proficiency: Demonstrate proficiency in biostatistics, and physicochemical and analytical methods. Research Excellence: Highlight your ability to plan and execute experimental trials, as well as your success in disseminating research findings through peer-reviewed scientific journals. Teamwork and Problem Solving: Exhibit an aptitude for collaborative work and problem- solving, which are essential for effective contributions to research teams. Language Skills: Possess excellent proficiency in English as a primary language of communication, with an understanding of French being a desirable additional skill. Applications and selection procedure: Cover Letter: Submit a cover letter that clearly specifies the position you are applying for and outlines your primary research interests. Comprehensive CV: Include a detailed Curriculum Vitae (CV) that highlights your academic and professional background, research experience, and relevant qualifications. Research Statement: Provide a concise research statement that summarizes your research goals and objectives, demonstrating your alignment with the position and the department's research priorities. Publication Table: Present a table listing your indexed publications, arranged in descending order from the most recent to the oldest. Include information about your authorship position (e.g., First position) and provide the following details for each publication: Journal Name (e.g., Sci. Total Environ.); Journal Quartile (e.g., Q1); Journal I-F (e.g., FI2022 = 10.9); H-Index (e.g., H = 317); Publisher (e.g., Elsevier) and the Digital Object Identifier (DOI). References: Include the contact information for three professional references who can vouch for your qualifications and potential as a researcher