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University of Coimbra

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Sustainability Impact Rated
Coimbra, Portugal
401–500th in World University Rankings 2026
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About the University of Coimbra

Basic information and contact details for the University of Coimbra

institution

Founded in 1290, the University of Coimbra (UC) is one of the oldest universities in the world and the oldest in all of Portugal. Up until the early part of the 20th century, it was also the only Portuguese-speaking university in the world. Built in the grounds of a former palace, its 16th century campus is classified as a UNESCO World Heritage site.

Located in the historic city of Coimbra, the university is home to over 21,000 students, 10% of whom are international students, placing it among Portugal’s most international universities and lending the city a cosmopolitan feel.

UC is organised across three campuses and comprises eight faculties that offer a large and diverse academic portfolio. The university is particularly popular with technology and science students and the university is home to the largest science faculty in the country.

In keeping with its 700 year history, the university emphasises tradition alongside modernity and innovation.

Key features on campus include a theatre, sports facilities and stadiums, a publishing house, an astronomical observatory, a baroque library and an 18th century bell tower. The university also oversees a number of museums, including a science museum and a museum of sacred art.

The university lays claim to a number of unique traditions such as Queima das Fitas (Ribbon Burning), to celebrate the end of studies, and the tying of tin cans to the legs of new students to welcome them to the university.

Coimbra is regarded as a safe and friendly city to live in. Dating back to the Roman era, it is the fourth largest city in the country, situated on a riverfront, where medieval architecture sits alongside modern buildings.

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Key Student Statistics

A breakdown of student statistics at the University of Coimbra

gender ratio
Student gender ratio
58 F : 42 M (1)
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International student percentage
19% (1)
student per staff
Students per staff
20.4 (1)
student
Student total
23217 (1)

Based on data collected for the (1) World University Rankings 2026

Jobs you might be interested in

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CBS - Post-Doctoral Position in Green and Sustainable Materials for Agronomic Applications

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


Institution: Mohammed VI Polytechnic University (UM6P) Department: Chemical and Biochemical Sciences - Green Process Engineering (CBS) Location: Benguerir/Jorf Lasfar, Morocco Duration: 12 months, renewable based on performance and funding. About Mohammed VI Polytechnic University Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa, striving to position itself among world-renowned universities. Located in the heart of the Green City of Benguerir, UM6P aims to make a significant national, continental, and global impact by driving economic and human development through cutting-edge research and innovation. The Chemical and Biochemical Sciences - Green Process Engineering (CBS) department focuses on advancing sustainable materials and technologies to address modern environmental and agricultural challenges. Position Description The post-doctoral researcher will contribute to projects focusing on the development and characterization of green and sustainable materials for advanced agronomic applications. These materials may include polymers, composites, or hybrid systems aimed at controlled-release fertilizers, biodegradable films, or environmentally friendly coatings. Key Responsibilities Research and Development: Design, synthesize, and characterize green or ecological materials for agronomic applications. Material Optimization: Develop functional materials, such as controlled-release fertilizers, films, or hydrogels, tailored to specific agricultural challenges. Characterization: Conduct structural (FTIR, XRD), thermal (TGA, DSC), morphological (SEM, AFM), and mechanical testing to evaluate material properties. Performance Evaluation: Implement agronomic trials to assess material performance under simulated or real environmental conditions. Scientific Communication: Prepare manuscripts for publication in high-impact journals and present findings at scientific conferences. Collaboration: Engage with interdisciplinary teams within UM6P and external partners to support collaborative research efforts. Mentorship: Co-supervise and mentor Master's and Ph.D. students, contributing to their academic and professional development. Qualifications and Experience Required: Ph.D. in Materials Science, Chemistry, Polymer Engineering, or a related field. Experience in the development of sustainable or green materials for advanced applications. Strong expertise in material synthesis and characterization techniques (e.g., FTIR, XRD, SEM, TGA, BET). Proven experience in data analysis and material performance optimization. Track record of publications in peer-reviewed journals. Preferred: Knowledge of agronomic applications such as controlled-release systems, biodegradable materials, or eco-friendly coatings. Experience with environmental or agricultural material testing. Skills and Attributes: Ability to work independently and collaboratively within a multidisciplinary team. Strong analytical, organizational, and scientific writing skills. Innovative mindset with a focus on developing sustainable solutions. Application Requirements Applicants are invited to submit the following documents: Cover letter detailing research interests, experience, and suitability for the position. Detailed curriculum vitae (CV). List of publications and patents. Contact information for two professional references. Benefits Opportunity to work within a dynamic and innovative research environment at UM6P. Access to state-of-the-art facilities for material synthesis, characterization, and testing. Collaboration with national and international research networks. Competitive salary and benefits package. This position is ideal for candidates passionate about sustainable materials and seeking to make a significant contribution to agronomic and environmental advancements.

Salary

Competitive

Posted

13 Mar 2026

ACER CoE - Postdoctoral Researcher in Membrane Desalination Processes

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


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. About the  project: This project aims to lower energy consumption and increase the water recovery of seawater desalination using the concept of desalination dilution by integrating a hybrid Forward Osmosis (FO) — Reverse Osmosis (RO) system. The work of this project includes lab work, computer modelling, life cycle assessment, and techno-economic study. The project will contribute to protecting water resources, promoting circular economic and zero liquid discharge concepts, and reducing the environmental impact of brine and unwanted water. The successful applicant will join a multidisciplinary research team who are working on a project funded by OCP Group. The successful postdoctoral applicant will manage an exciting project on membrane processes technology and small-scale testing for seawater desalination. He/she should demonstrate experience in membrane processes, water quality analysis, and lab and pilot-scale testing of water treatment and desalination processes. Required qualifications: The successful postdoctoral applicant will manage an exciting project on hybrid FO-RO desalination system and small-scale testing for seawater desalination applications. The candidate should have a PhD in Engineering (including Environmental, Civil or Chemical Engineering), Material Science or any other relevant field. The candidate should have excellent experimental and analytical skills relevant to the project (assessment of membrane processes and water quality analysis) are required. Experience in computational fluid dynamics modelling of water treatment and desalination processes is an advantage. Willingness to work within a multidisciplinary group. Demonstrated skills in scientific writing in the form of research journal articles, conference papers, or high-quality scientific reporting. Innovative, driven, out-of-the-box thinker, well-organized, self-motivated to investigate and implement new ideas, and proactive in overcoming obstacles. Good communication and presentation skills in English. French is an advantage. Skills in problem solving, analytical thinking, and planning. How to apply: Applications should contain a motivation letter and a detailed curriculum vitae with a list of two references and their contact information. The motivation letter and CV should be written in English. The UM6P embraces inclusion and diversity as key values. We are fully committed to removing any descriminatory barrier related to gender, and not only, in the recruitment and career progression of our staff and studenst. UM6P.

Salary

Competitive

Posted

13 Mar 2026

CAS - Postdoctoral Researcher in African Anthropology, Environment and Health

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


Département / Department :  Unité / Unit: Center for African Studies Université / University: Mohammed VI Polytechnic University  Intitulé de l’offre Postdoc / Title of the Postdoc offer: African Anthropology: Environment and Health Summary of the subject: One of the missions of the Center for African Studies is to archive contemporary research on the African continent. The candidate must know Arabic and be familiar with the work of Mokhtar Soussi. This work focuses on southern Morocco and Souss culture. It mentions links with sub-Saharan Africa. The post-doctoral candidate will need to identify all these links 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.

Salary

Competitive

Posted

13 Mar 2026

CBS - Postdoctoral Research Fellow in Microbiome Dysbiosis and Disease Mechanisms

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


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)

Salary

Competitive

Posted

13 Mar 2026

VANGUARD - Postdoc in Network Tensor Completion

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


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.

Salary

Competitive

Posted

13 Mar 2026

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Subjects Taught at the University of Coimbra

See below for a range of subjects taught at the University of Coimbra

Arts and Humanities

  • Archaeology
  • Architecture
  • Art, Performing Art and Design
  • History, Philosophy and Theology
  • Languages, Literature and Linguistics

Business and Economics

  • Accounting and Finance
  • Business and Management
  • Economics and Econometrics

Computer Science

  • Computer Science

Education Studies

  • Education

Engineering

  • Chemical Engineering
  • Civil Engineering
  • Electrical and Electronic Engineering
  • General Engineering
  • Mechanical and Aerospace Engineering

Law

  • Law

Life Sciences

  • Agriculture and Forestry
  • Biological Sciences
  • Sport Science

Medical and Health

  • Medicine and Dentistry
  • Other Health

Physical Sciences

  • Chemistry
  • Geology, Environmental, Earth and Marine Sciences
  • Mathematics and Statistics
  • Physics and Astronomy

Psychology

  • Psychology

Social Sciences

  • Communication and Media Studies
  • Geography
  • Politics and International Studies
  • Sociology