University of Twente

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.

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 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, in particular 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 in order to propose new original alternatives in terms of efficiency, environmental friendliness and sustainability. Job Description We are seeking a highly motivated and qualified post-doctoral researcher in organic/inorganic chemistry to join our research team for an exciting project focused on the development of novel synthetic methods for the production of phosphorus derivatives. These derivatives play a crucial role in various industrial applications, including fine chemistry, catalysis, agriculture, and life science. For instance, phosphorus-based chemicals are essential in hydrometallurgy, ceramics, and serve as building blocks for RNA and DNA. Additionally, their synthetic analogues are critical clinical drugs for treating a wide range of diseases, including hepatitis C virus and Covid-19. Expertise in coordination chemistry and/or process developement would be a plus for this position. Responsibilities: As a Post-Doctoral Researcher, your responsibilities will include: Green Synthetic Methods: Conducting research to establish innovative and environmentally friendly synthetic methodologies for accessing a diverse range of phosphorus derivatives. This will involve the creation of phosphorus–carbon bonds using techniques such as photochemical reactions, mechanochemistry, multi-component reactions, atoms and steps economy, and both homogeneous and heterogeneous catalysis. Experimental Validation: Designing and performing experiments at both laboratory and pilot scales to validate the feasibility and scalability of the developed synthetic processes for potential industrial applications. Organometallic and Phosphorus Chemistry: Applying your expertise in organometallic and phosphorus chemistry to design and develop synthetic methodologies, analyze chemical structures, and characterize synthesized compounds. Sustainability: Ensuring that all research activities align with green and sustainable principles, with a focus on reducing the environmental impact associated with phosphorus derivative synthesis. Publication and Reporting: Collaborating with the research team to write scientific reports, prepare research publications, and effectively communicate results and data analysis in both French and English. Candidate Criteria Ph.D. in Chemistry, Organic Chemistry, or a related field, accompanied by a distinguished record of research accomplishments. Demonstrated research experience in the area of green chemistry and organic phosphorus derivatives is essential. This may include published papers, conference presentations, or a strong thesis on the topic. Proficiency in organic synthesis techniques and methodologies is crucial, as you'll likely be working on designing and synthesizing novel phosphorus-containing compounds. Proficiency in various analytical techniques such as NMR spectroscopy, mass spectrometry, IR spectroscopy, and HPLC, which are commonly used to characterize organic compounds.  Proven excellence in teaching and mentorship, evidenced by innovative pedagogical approaches and contributions to student development. Strong communication and collaboration skills, with a commitment to interdisciplinary research and innovation. Alignment with UM6P's mission of promoting sustainable economic development through research and innovation. ​Application and Selection: The application folder must contain: Detailed CV, Cover letter along with a synthetic presentation of the background, research works, projects and activities, publications, key achievements, Research and teaching plans, entrepreneurial ideas and concepts if any, and services to UM6P community: max 3-4 pages, 3 reference letters. UM6P.

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.