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University of Tunis El Manar

Ranked
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Sustainability Impact Rated
Rommana, Tunisia
801–1000th in World University Rankings 2026
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About the University of Tunis El Manar

Basic information and contact details for the University of Tunis El Manar

institution

University of Tunis El Manar (UTM), founded in 2000, offers a wide range of degrees in law, literature, environmental sciences, health sciences, medicine, economics, engineering and technology, sciences, humanities, IT, social sciences. It is one of the best universities in Tunisia.

UTM’s partners include Université Paris-Dauphine, University Blaise Pascal-Clermont-Ferrand II, University Paris 1 Panthéon Sorbonne in France, University of California in the US, and The Berlin School of Economics and Law and Bremen University in Germany.

Students can take part in swimming, tennis, dance, aerobics, basketball and football on campus. UTM also organises an annual arts and sports festival involving music, poetry, painting, tennis, chess, handball and swimming, as well as a Science Festival with round tables, debates, trips to laboratories and natural sites, and film screenings. In addition, UTM is located in Tunis - the Tunisia's capital city with the highest concentration of students, given it hosts six universities.

As a capital city, Tunis has a rich nightlife and history. Its medina, dating from the eighth century, is made of narrow streets with stray cats and artisan shops, all leading to the mosque. The old Carthage amphitheatre hosts an annual festival of performing arts. The Bardo Ottoman palace prides itself on its possession one of the biggest collections of Roman mosaics in the world. Twenty kilometers away, the village of Sidi Bou Saïd, painted by Paul Klee and August Macke, can be a mesmerising blue and white weekend getaway.

Famous alumni include Tunisian children’s author Samar Samir Mezghanni, Tunisian lawyer, politician, and former Prime Minister, Samia Abbou, and former Prime Minister Mehdi Jomaa.

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Key Student Statistics

A breakdown of student statistics at the University of Tunis El Manar

gender ratio
Student gender ratio
75 F : 25 M (1)
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International student percentage
10% (1)
student per staff
Students per staff
8.1 (1)
student
Student total
16341 (1)

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

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Lecturer (ARTT), Academy of Visual Arts

HONG KONG BAPTIST UNIVERSITY

Hong Kong Baptist University

Hong Kong

institution

Hong Kong Baptist University

Hong Kong


Job Description SCHOOL OF CREATIVE ARTS ACADEMY OF VISUAL ARTS Part-time Lecturer (25260664) The Academy of Visual Arts is the first-of-its-kind local institution in delivering Arts and Technology education, which is looking for Part-time Lecturer(s) to teach the course(s) at undergraduate level in the following areas: Unreal VR technology Digital media and fabrication Creative computation Any other related disciplines The ideal candidate should hold a master’s degree or above in related disciplines, with 3 years of experience in creative industries with aspects of content development, budgeting, licensing, administration, marketing, or audience engagement, preferably with teaching experience at the university level. A good command of English and Chinese, excellent communication skills, and a strong sense of responsibility are required. Duties may also include supervision of students, marking of examination papers, and any other work as assigned by the Programme Director and Director of the Academy. The initial appointment will be offered on a part-time basis commencing Sep 2026. Re-appointment thereafter will be subject to performance review and course availability. Salary will be commensurate with qualifications and experience. Application Procedure: Applicants are invited to submit their applications at the HKBU e-Recruitment System. Those who are not invited for an interview 8 weeks after submission of the application may consider their applications unsuccessful. Details of the University’s Personal Information Collection Statement can be found at https://hro.hkbu.edu.hk/en/worklife-at-hkbu/employee-favourable-environment.html#privacy-policy. The University reserves the right not to make an appointment for the post advertised, and the appointment will be made according to the terms and conditions applicable at the time of offer. Review of applications is ongoing until the position is filled.

Salary

Competitive

Posted

17 Apr 2026

Interim Change Programme Communications Lead

CRANFIELD UNIVERSITY

Cranfield University

United Kingdom, Bedford

institution

Cranfield University

United Kingdom, Bedford


Organisation: Cranfield University Faculty or Department: Communications and External Affairs Based at: Cranfield Campus, Cranfield, Bedfordshire Hours of work: 37 hours per week, normally worked Monday to Friday. Flexible working will be considered Contract type: Fixed term contract Fixed Term Period: For 6 Months Salary: Full time starting salary is normally in the range of £48,760 to £58,664 per annum, with potential progression up to £71,050 per annum Apply by: 26/04/2026 Role Description About the Role This role is responsible for leading and delivering communications across a complex change programme, ensuring colleagues are clearly informed, appropriately engaged and supported through transition. Working closely with senior leaders, you will translate complex and sensitive information into clear, consistent messaging, support consultation processes, and help maintain trust during a period of organisational change. About You You will be educated to degree level or have equivalent professional experience in communications, organisational development or a related field. You will have experience delivering communications within organisational change or transformation programmes, ideally within a complex, multi-stakeholder environment such as higher education, public sector or similar. With excellent written and verbal communication skills, you will be confident translating complex information into clear, accessible messaging and producing high-quality communications for senior audiences. You will have strong stakeholder management skills and the ability to influence and advise senior leaders, particularly in relation to sensitive or challenging situations. You will be able to manage multiple priorities in a fast-paced environment, demonstrate sound judgement, and operate with professionalism, discretion and emotional intelligence. Experience of consultation processes or employee relations contexts would be advantageous. About Us As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here. Our Values and Commitments Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here. We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity Working Families. Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here. Working Arrangements Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners. How to apply For an informal discussion about this opportunity, please contact Jonathan Walker, Director of Communications and External Affair via Jonathan.Walker@cranfield.ac.uk / +44 1234 75 4464 or Charly Guildford, People & Culture Business Partner via Charly.Guildford@cranfield.ac.uk / +44 1234 75 4226 Please do not hesitate to contact us for further details on E: hrrecruitment@cranfield.ac.uk. Please quote reference number xxx. Interviews to be held: ASAP Please note that we reserve the right to close this advert and interview prior to the stated closing date should we receive sufficient numbers of applications. Therefore, we would encourage you to complete and submit your application as soon as possible.

Salary

£48,760 to £71,050 per annum

Posted

17 Apr 2026

Research Fellow / Engineer (Steel Structures and AI) - ZLL1

SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)

Singapore Institute of Technology (SIT)

Singapore

institution

Singapore Institute of Technology (SIT)

Singapore


As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. Key Responsibilities Participate in and manage research projects with the Principal Investigator (PI), Co-PI and research team members to ensure all project deliverables are met. Support research activities in one or more of the following areas: i. Advanced welding and automation technologies for steel fabrication and construction ii. Experimental investigation of high-strength aluminium alloy structures iii. Development and testing of lightweight and long-span earth retaining and stabilising structures iv. AI-enabled structural analysis, optimisation and design tools for high-efficiency, low-carbon composite building systems Plan and conduct experimental work, including but not limited to: i. Material and component testing ii. Structural behaviour testing of steel and aluminium members/connections iii. Fabrication trials and validation of welded structural components iv. Data acquisition, instrumentation and monitoring during laboratory testing Perform numerical modelling and simulation, such as finite element modelling, parametric studies, and calibration against test data. Analyse experimental and numerical results, and prepare technical reports, presentations and publications. Assist in the development of design methodologies, engineering recommendations, and data-driven or AI-enhanced workflows for structural applications. Coordinate procurement, laboratory set-up, testing schedules, and liaison with vendors/suppliers and industry collaborators. Communicate with relevant internal and external stakeholders to ensure project deliverables and milestones are achieved. Carry out risk assessment and ensure compliance with Work, Safety and Health regulations. Work independently, as well as within a multidisciplinary team, to ensure proper operation and maintenance of equipment and research facilities. Support grant reporting, project documentation, intellectual property development, and other ad hoc duties as assigned. To communicate in any relevant internal or external stakeholders to ensure project deliverables are met. Any ad-hoc duties assigned by Supervisor. Job Requirements Master’s degree in Civil Engineering, Structural Engineering, Mechanical Engineering, Materials Engineering, or a related discipline. Demonstrated knowledge in at least one of the following areas: Structural steel or aluminium structures Welding, fabrication, or construction automation Experimental structural testing and instrumentation Numerical modelling and simulation AI/data-driven methods for engineering applications Familiarity with engineering software such as ABAQUS, ETABS, MATLAB, Python, or equivalent will be an advantage. Prior experience in laboratory testing, data analysis, or industry-related engineering projects will be an advantage. Key Competencies Ability to build and maintain strong working relationships with internal and external stakeholders. A self-directed learner with a strong commitment to continuous learning and professional development. Strong technical writing and presentation skills. Excellent analytical and critical thinking abilities. High level of initiative, responsibility, and ownership of work. Ability to work effectively both independently and within multidisciplinary research teams. Good project coordination and time management skills. Strong interest in applied research with industry relevance and real-world impact.

Salary

Competitive

Posted

17 Apr 2026

Doctoral Researcher, Cancer Data Science

UNIVERSITY OF HELSINKI

University of Helsinki

Finland, Helsingfors (Helsinki)

institution

University of Helsinki

Finland, Helsingfors (Helsinki)


University of Helsinki, Faculty of Medicine invites applications for the position of  Doctoral Researcher  in the Cancer Data Science group led by Associate Professor Mariike Kuijjer, at the iCAN Flagship in Digital Precision Cancer Medicine at the Faculty of Medicine, University of Helsinki. The position is funded through a project by the Sigrid Jusélius Foundation titled “Regulatory determinants of metastatic progression in high-grade serous ovarian cancer.” The ideal starting date is summer or early fall 2026, but this is flexible and can be discussed. The appointment is a full-time position and is made for a period of three years with possible extension depending on future funding. Our research The Kuijjer group was established in 2018 at the University of Oslo and expanded to the University of Helsinki in 2025. The group focuses on developing computational and data science approaches to increase our understanding of gene regulation and how rewiring of gene regulatory networks can influence cancer development, progression, and disease heterogeneity. The group's current projects use network science and artificial intelligence to develop tools that (i) integrate multi-modal data, (ii) model gene regulation at increased genomic and cellular resolution, (iii) refine the analysis of genome-wide regulatory networks. The group applies these tools to study various cancer types, including ovarian cancer. For more information, visit kuijjerlab.org. About the roleThe advertised project aims to identify regulatory determinants of ovarian cancer progression through regulatory network modeling and analysis. The selected candidate will apply and extend network modeling approaches developed in the Kuijjer group to model patient- and cell type-specific gene regulatory networks using bulk and single-cell ovarian cancer data. These networks will be analyzed to define patient-specific regulatory heterogeneity in primary ovarian cancer, identify regulatory rewiring that drives metastatic progression, characterize the regulatory mechanisms modulated by therapeutic pressure, and assess how these programs relate to therapy response. The project will leverage various publicly available datasets as well as data from the in-house Oncosys-OVA study led by our collaborator Prof. Anniina Färkkilä, University of Helsinki. Overall, the project combines methodological development with biological discovery, offering opportunities to contribute both to computational innovation and to mechanistic insights into ovarian cancer progression. The candidate We seek a highly motivated candidate with strong computational skills in the field of high-throughput omics data analysis, comparative genomics, functional genomics, or related fields. The candidate is excited about applying computational tools to answer questions in cancer research. They are collaborative and creative, and have strong programming skills dedicated to the analysis of large-scale genomics data. Experience with the analysis of omics data is required for this position. Knowledge of cancer biology is a strong advantage. Experience with high-performance computing, genomic data integration, biological network analysis, and/or gene regulation is desirable, but not required.  The position is open to applicants with a Master's degree in computational biology, bioinformatics, biostatistics, cancer genomics, network science, or related fields. Candidates who are finishing their Master's thesis are also welcome to apply. They should mention the expected date of their defense and steps that need to be completed to finish their thesis in the cover letter. Qualification requirements Master's degree in computational biology, bioinformatics, biostatistics, cancer genomics, network science, or a related field. Applicants with a background in biology or (bio)medicine are welcome to apply, provided they have documented expertise in computational biology Proficiency in programming (such as Python, R, Bash) Experience with analysis of high-throughput omics data is required Knowledge of cancer biology is a strong advantage Experience with genomic data integration, biological network analysis, and/or gene regulation is an advantage Experience with high-performance computing is desirable Strong analytical and problem-solving skills Teamwork skills and the willingness to collaborate, share ideas, and contribute to a multidisciplinary research environment spanning Helsinki and Oslo Strong communication skills in English, with both written and verbal proficiency The appointee should either already have the right to pursue a doctoral degree at the University of Helsinki by the start of the appointment or apply for the right and obtain it within the probationary period of six months of their appointment. If the candidate does not already have the right to pursue a doctoral degree at the University of Helsinki, it must be applied for separately: www.helsinki.fi/en/research/doctoral-education/the-application-process-in-a-nutshell. The requirements for pursuing a doctoral degree at the University of Helsinki can be found at https://www.helsinki.fi/en/research/doctoral-education/eligibility-and-educational-documents. The chosen applicant is expected to reside in Finland while employed by the University of Helsinki.What we offer A salary of 2600 – 2800 €/month depending on the candidate's qualifications A professional, stimulating working environment The University of Helsinki also offers comprehensive services to its employees, including occupational health care and health insurance, unemployment and pension fund, a generous holiday package, sports facilities, and opportunities for professional development: https://www.helsinki.fi/en/about-us/careers. How to apply Applications should be submitted through the University of Helsinki Recruitment System via the "Apply now" button. Internal applicants (i.e., current employees of the University of Helsinki) submit their applications by using the Employee Login button. The application must include: A cover letter, stating your motivation, scientific background, documented experience with large-scale genomic analyses, and research interests A detailed CV with a list of publications and other research output, if applicable 2-3 references (name, institution, e-mail, telephone number, and relation to the candidate) These should be uploaded in .pdf format. Applicants may also upload their Master’s thesis or other representative research work, if available. Please submit your application through the web-based recruitment system linked in the announcement. Although the recruitment system includes a basic CV, we ask candidates to also include a separate, detailed CV in .pdf format with their application. Applications without a cover letter and/or detailed CV will not be considered further.  The closing date for applications is 31.5.2026. Inquiries about the position can be directed to Mariike Kuijjer: mariike.kuijjer@helsinki.fi. If you need technical support with the recruitment system or additional information about the application process, please contact HelsinkiUni Help, uni-help@helsinki.fi.  About us The University of Helsinki (UH), founded in 1640, is a vibrant scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities and ranks among the top 100 international universities in the world. It is currently investing heavily in life sciences research. UH offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development.  The Faculty of Medicine promotes high quality scientific research. It provides research-based undergraduate and postgraduate education in medicine, dentistry, psychology and logopedics, and an international Master's Program in Translational Medicine. It also offers psychotherapist education. In addition to its teaching and research activities, the Faculty serves as a significant expert organization in the healthcare sector and contributes to the discourse on ethics in the field. The Faculty aims to be one of the best medical research faculties in the world, while rein-forcing its status as a distinguished institution of multidisciplinary education in healthcare.  The Faculty of Medicine at the University of Helsinki constitutes the academic medical center together with HUS Helsinki University Hospital and the Helsinki Institute of Life Science (HiLIFE). This medical center has been successful in international comparisons, ranking among the top 10 medical campuses in Europe and the top 50 globally. A diverse and equitable study and work culture is important to us. That is why we do our best to promote an inclusive university community. We encourage all qualified applicants from diverse backgrounds to apply for our positions. Click this link to read about accessibility and inclusivity at our University. JOIN US TO BUILD A BETTER WORLD – TOGETHER! #HelsinkiUniCareers

Salary

2600 – 2800 €/month

Posted

17 Apr 2026

Research Fellow – Machine Learning for Nanoscale Semiconductor Manufacturing

UNIVERSITY OF SOUTHAMPTON

University of Southampton

United Kingdom, Southampton

institution

University of Southampton

United Kingdom, Southampton


Semiconductor fabrication is one of the most complex and precision-driven forms of manufacturing. At nanometre scales, even subtle variations in process conditions can introduce defects that degrade device performance, reduce yield, and drive up production costs. Addressing this challenge requires new modelling approaches that can capture the full complexity of fabrication processes and enable optimisation before physical manufacturing begins. This project aims to develop advanced deep learning models capable of predicting fabrication outcomes and guiding fabrication recipe optimisation. By learning directly from experimental and process data, these models will enable a shift from iterative, trial-and-error fabrication towards predictive and data-driven manufacturing. We are seeking a highly motivated Machine Learning Researcher to join a multidisciplinary team of fabrication engineers and AI specialists at the University of Southampton, within the School of Electronics and Computer Science, working in the group of Dr Yasir Noori. In this role, you will work at the interface of machine learning and semiconductor engineering, developing models that predict post-fabrication device characteristics from process parameters. You will engage with complex, high-dimensional datasets derived from real fabrication workflows, including microscopy, spectroscopy, and electrical performance measurements. You will work closely with fabrication engineers to translate physical processes into machine learning models, design and train deep learning architectures, and evaluate their ability to generalise across different process conditions. The models you develop will not remain confined to the research lab, but will be validated experimentally and tested at an industrial scale in collaboration with global companies in semiconductor fabrication and electronic design automation. The position offers a rare opportunity to apply machine learning to an important technical challenge with substantial potential impact. You will also be involved in supervising PhD students and junior researchers and play a central role in shaping the research direction of the team. Your work is also expected to contribute to the development of innovative technologies with a clear pathway to commercialisation through the spinout company Deep Fabrication, to influence how semiconductor manufacturing is approached in practice. The role will provide you with deep exposure to nanofabrication processes, experience working with industry-relevant datasets and problems, and the opportunity to publish in leading journals and conferences. It is particularly well-suited to candidates who are motivated by applying machine learning to real-world systems where the underlying physics is complex and not fully understood. This position is offered for 24 months in the first instance, with the possibility of extension for a further 12 months. To apply, please submit your CV and a cover letter outlining how your experience and interests align with the aims of the project, and provide responses to the short-listing questions.

Salary

£36,636 to £44,746 per annum

Posted

17 Apr 2026

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Subjects Taught at the University of Tunis El Manar

See below for a range of subjects taught at the University of Tunis El Manar

Arts and Humanities

  • Archaeology
  • 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
  • Veterinary 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