Jose Rizal University

At the University of Vienna, over 10,000 people work together on the big questions of the future. Approximately 7,500 of them are academic staff members. These are individuals who, with their curiosity and their continuous pursuit of excellence, engage in international cutting-edge research and teaching. With us, you will also find space to unfold your potential. We are looking for a/an  University Assitant (praedoc) - Completion Contract 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.08.2026 Reference no.: 5544 Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as personalities who need space for their continuous striving and curiosity in order to be able to be More than 7,500 academics at the University of Vienna thrive on continuous exploration and curiosity and help us better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere of influence: The Doctoral School Computer Science DoCS (https://docs.univie.ac.at) founded in 2020 offers a structured doctoral programme that supports early-career research in the areas of Computer Science and Business Informatics. The programme includes world-leading researchers in Computer Science as supervisors and co-supervisors who pursue basic as well as applied research within an intensive doctoral teaching programme tailored to the scientific needs of students in small topical groups. The Doctoral School Computer Science provides the option of performance-based contract extensions to doctoral students who previously had a position as university assistant (prae doc) or as third-party funded researcher (prae doc) at the University of Vienna. This completion contract is meant to support a high-qualified DoCS fellow in the final phase of the doctoral studies. The successful applicant will get a contract as university assistant (prae doc) and will be working in the research group Data Mining and Machine Learning at the Faculty of Computer Science. The group’s research focuses on data mining - particularly clustering and representation learning - graph mining, and probabilistic machine learning. We place great emphasis on a relaxed, collaborative environment and a collegial atmosphere. Social interaction is a top priority for us and contributes to active scientific dialogue and a positive work environment. Learn more about us at https://dm.cs.univie.ac.at/ Your future tasks: You will actively participate in research, teaching, and administration. This includes, among other things: Your primary responsibility is to complete and submit your dissertation. You will develop new methods in data mining and machine learning, particularly in the areas of clustering representation learning graph mining anomaly detection You will contribute to research projects and scientific studies in the above-mentioned areas. You will independently teach courses in accordance with the provisions of the collective bargaining agreement or assist in doing so. You will publish internationally and give presentations. You will contribute to the organization of meetings, conferences, and symposia. You will participate in faculty, teaching, and research administration.  This is part of your personality: Required Qualifications: You hold a degree in Computer Science or Computer Engineering (Diplom, Master’s, or Magister degree), and a solid foundation in computer science is required. You are currently enrolled in a doctoral program (Computer Science or Business Informatics) at the University of Vienna and are a member of the Doctoral School of Computer Science. You have demonstrated outstanding academic performance (e.g., FÖP within one year, annual submission of progress reports, exceptional publication record). You possess a high degree of motivation and commitment to successfully complete your doctoral studies within the intended timeframe. You have proven expertise in one or more of the following areas: Clustering Representation Learning Graph Mining Anomaly Detection You possess teaching skills and experience with e-learning. You have excellent written and spoken English skills (at least C1 level). (The language of communication within the team is English!) Desirable qualifications: You have publications in leading journals in the field, e.g., ICCV, KDD, ICDM, WWW You are a team player with strong social and communication skills. You work independently and reliably. You have knowledge of university processes and structures. You have international experience You have teaching experience What we offer: Work-life balance: Our employees enjoy flexible working hours and can partially work remotely. Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment. Good public transport connections: Your workplace is easily accessible by public transport. Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Fair salary: The basic salary of EUR 3.776,10 (on a full-time basis) increases if we can credit professional experience. Equal opportunities for everyone: We look forward to diverse personalities in the team! It is that easy to apply: Resume Cover letter outlining your ideas for a potential doctoral project Abstract of your master’s thesis Degree certificates and transcripts with grades from your bachelor’s and master’s programs List of publications, proof of teaching experience (if applicable) If you have any questions, please contact: Claudia Plant claudia.plant@univie.ac.at We look forward to new personalities in our team! The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We lay special emphasis on increasing the number of women in senior and in academic positions among the academic and general university staff and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. University of Vienna. Space for personalities. Since 1365. Data protection Application deadline: 04/25/2026 Prae Doc

Department: Department of Mathematics and Statistics – Faculty of Science Deadline: 16 May 2026 Start date: 1. 6. 2026 Job type: part-time Job field: Education and schooling Dean of the Faculty of Science, Masaryk University announces an open competition for the position Lecturer in Mathematics Workplace: Department of mathematics and statistics, Faculty of Science, Masaryk University, Czech Republic Type of Contract: temporary position with 3-year contract (with possible extension), academic Working Hours: 0.1 FTE (part-time employment of 4 hours per week) Expected Start Date: 1. 6. 2026 or negotiable with respect to immigration timelines for non EU candidates Number of Open Positions: 2 Application Deadline: 16. 5. 2026 EU Researcher Profile: R2 About the Workplace Masaryk University is modern, dynamic and the most attractive university in the Czech Republic with ten faculties, more than 7 000 staff and 33 000 students, a wide range of research areas and a strong international position. We are the largest academic employer in the South Moravian Region. Faculty of Science MU, a holder of the HR Excellence in Research Award by the European Commission, is a research-oriented faculty, offering university education (Bachelor’s, Master’s, and Doctoral degree programs) closely linked to both primary and applied research and high school teaching of the following sciences: Mathematics, Physics, Chemistry, Biology, and Earth sciences. We are the most productive scientific unit of the Masaryk University generating around 40 % of MU research results. Department of mathematics and statistics at the Faculty of Science MU is the faculty’s main mathematics department, providing teaching in all areas of mathematics for most of the university’s faculties. It serves as the center for mathematical research at Masaryk University. Job Description Key Duties: Teaching lectures and seminars in various areas of pure and applied mathematics Supervising and reviewing bachelor’s and master’s theses Consulting with students Skills and Qualifications The applicant must have: PhD in mathematics Experience teaching university-level mathematics Ability to teach in Czech Good command of English (spoken and written) The applicant should have: Experience teaching at the high school level Experience in research Informal inquiries about the position can be sent to Prof. Petr Hasil, e-mail hasil@math.muni.cz, phone +420 549 491 480. We Offer An interesting job in a dynamically-expanding university area Flexible working hours and occasional home office to support personal needs in family and career compatibility Employee benefits such as 8 weeks of paid vacation per year, pension insurance contribution/long-term investment product/nursery/children´s group allowance, lunches in canteens of MU, Multisport card, psychological counselling, vaccinations free of charge, discounted language courses, exclusive mobile tariff offer by Vodafone, childcare groups at Campus and Komenského náměstí) Opportunity to work and live in a modern and dynamic city (for more information on costs of living, you can refer to Numbeo) Welcome Office provides support with your relocation to Brno Application Process The application shall be submitted online by 16. 5. 2025 via an e-application, please find the reference to the e-application in the beginning and end of the advertisement. The candidate shall provide following: CV Cover letter describing candidate's teaching interest and experience Overview of theses supervised and defended, courses taught, research results and publications Names and contact details of at least 2 references. After submitting your application successfully, you will receive an automatic confirmation email from jobs.muni.cz. Selection Process Received applications will be considered carefully in line with principles of the EU Charter and Code for Researchers. Selection criteria: (i) meeting qualification requirements described above, (ii) all required documents provided. Shortlisted candidates will be invited for a personal or online interview. The Faculty Recruitment Policy (OTM-R) can be seen here. Faculty of Science, Masaryk University is an equal opportunity employer. We support diversity and are committed to creating an inclusive environment for all employees. Visit our Career page. We are looking forward to hearing from you!

Novel Fibre Reinforced Polymer–Steel–Concrete Transition Structures for Offshore Wind Turbines (FRESCO) is a new research project funded by the Supergen Offshore Renewable Energy Hub. It aims to develop a novel glass fibre-reinforced polymer (GFRP)–steel–concrete tower-to-monopile transition structure for offshore wind turbines, with a focus on improving structural efficiency, durability, and ease of installation. Your work will include the development of advanced numerical models of the transition system, alongside the testing of a scaled prototype structure to demonstrate proof of concept. You will lead the technical activities related to modelling and experimental testing, including the design of test programmes and interpretation of results. The role will also involve analysing and synthesising findings, contributing to design recommendations, and disseminating outcomes through publications and engagement with relevant industry stakeholders and events.You are invited to contact Dr Sheida Afshan (s.afshan@soton.ac.uk ) for further information about this position in advance of submitting your application. Applicants should hold a PhD in Structural Engineering or equivalent professional qualifications and experience with previous relevant experience in computational modelling and experimental testing. Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification.