École centrale de Lille

At the University of Vienna almost 11,000 personalities work together towards answering the big questions of the future. Around 3,000 of them contribute to enabling excellent research and teaching through their expertise and work in administration and organisation. They know how they can work best. Flexible, remote and with as much freedom as they need to develop their potential. You know, too? We are seeking a/an Technician 47 Faculty of Psychology Startdate: 01.05.2026 | Working hours: 40 | Collective bargaining agreement: §54 VwGr. IIIb Limited until: 31.10.2026 Reference no.: 5513 The Faculty of Psychology is seeking to fill the position of a technician to oversee the transition of several research positions from the Vienna Cognitive Science Hub to the faculty. This cross-faculty and cross- departmental role is assigned to the Department of Cognition, Emotion, and Methods in Psychology. The advertised position is for 40 hours per week and is limited to 6 months. Your personal sphere of influence: The members of the Faculty of Psychology engage in research and teaching focused on describing and explaining human experience and behavior, as well as changes therein. Based on integrative and complementary research approaches from neuroscience, cognitive science, and the social sciences, the goal is to make theoretically grounded and empirically testable contributions to scientific knowledge and its transfer. The Department of Cognition, Emotion, and Methods in Psychology consists of approximately 100 staff members organized into eight research units with laboratories equipped with EEG, fNIRS, VR, eye-tracking, physiology, and brain stimulation systems. Our international team places great value on respectful interaction and independent work. Your future tasks: Supporting the transition of researchers from the Vienna Cognitive Science Hub to the Faculty of Psychology as a replacement for the previous technical support provided by a data scientist. Transfer of collected scientific data, data backup/cloud-based infrastructure for collected data and study-related products. Assisting with the organization and post-processing of collected raw data for use in ongoing projects within the context of the Study Participant Platform (SPP). In particular, advanced statistical analysis methods (latent profile analysis, network analysis) and statistical software packages will be utilized. Administrative support for managing specialized software and transferring/developing analyses to open-source software. Support in presenting research on the Vienna CogSci Hub’s Transition website. This is part of your personality: General or vocational secondary school (upper level) Programming skills: R, SPSS required; MatLab, MPlus, etc. are a plus Excellent written and spoken English Excellent communication skills and strong verbal and written expression Knowledge of latent profile analysis and network analysis is a plus Knowledge of eye-tracking and fNIRS is a plus Knowledge of project management and field studies is a plus Research experience in experimental/empirical methods is a plus You should be a team player What we offer: Work-life balance: Our employees enjoy flexible, family-friendly working hours, remote/hybrid and/or part-time work (upon agreement). Inspiring working atmosphere: You are part of a committed team with diverse university backgrounds in a relaxed work environment. Good public transport connections: Your workplace in the center of beautiful Vienna is easily accessible by public transport. Internal further training: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Fair salary: Salary will be paid in accordance with the Collective Bargaining Agreement of the University of Vienna. The basic salary of EUR 3,131.30 (III b) based on full-time employment, paid 14 times per year, increases based on professional experience. The advertised position is for 40 hours per week and is limited to 6 months.  Equal opportunities for all: We welcome every additional/new personality to the team! It’s that easy to apply: With your CV & letter of motivation (max. 2 pages) Certificates Via our job portal / apply button If you have any content questions, please contact: Matthew Pelowski matthew.pelowski@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 place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, 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: 04/10/2026 Laboratory & Technology

City University of Hong Kong is a dynamic university located in the heart of Hong Kong. As a publicly funded institution, our goals are to pursue high levels of excellence, promote innovation and nurture creativity with the aim to improve people’s lives. In a city where East meets West, our vision is to become globally recognised for professional education, one that emphasises the mutual enrichment of different cultures and intellectual traditions, and for research that makes a real difference. The University comprises ten Colleges/Schools, including Biomedicine, Business, Computing, Creative Media, Energy and Environment, Engineering, Law, Liberal Arts and Social Sciences, Science, and Veterinary Medicine and Life Sciences. Our curricula are designed to promote knowledge creation, original discoveries and innovative thinking. We nurture tomorrow’s global leaders through Inspirational Learning, Interactive Learning and Innovative Learning. Applications and nominations are invited for : Head of Department of Public and International Affairs [Ref. R/276/25] The Position Reporting to the Provost and Deputy President through the Dean of College of Liberal Arts and Social Sciences, the Head of Department will provide leadership and strategic direction in research and professional education for the Department. The Head will encourage and promote academic excellence, and steer the Department to enhance the mission and vision of the University in alignment with the University’s Strategic Plan. The Person The appointee should have a distinguished record of research, teaching and scholarship, and substantial relevant experience in tertiary education; outstanding management effectiveness; commitment to teamwork; and strong communication and networking skills to build and nurture internal and external contacts to the benefit of the Department. A doctoral degree with strong academic and professional qualifications is required. Salary and Conditions of Service The appointee will be offered appointment to an academic rank commensurate with qualifications and experience. The headship appointment will be on a concurrent basis for an initial period of about three years. An attractive remuneration package, driven by market competitiveness and individual performance, will be offered. Excellent fringe benefits include gratuity, leave, medical and dental schemes, and relocation assistance (where applicable). Information and Application Further information on the post and the University is available at http://www.cityu.edu.hk, or from the Human Resources Office, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong [Email : hrpiasearch@cityu.edu.hk /Fax : 2788 1154 or 3442 0311]. To apply, please submit an online application and include a current curriculum vitae. Nominations can be sent directly to the Human Resources Office, or by email to "hrpiasearch@cityu.edu.hk". Applications and nominations received by 25 April 2026 will receive full consideration. The University’s privacy policy is available on the homepage. City University of Hong Kong is an equal opportunity employer. We are committed to the principle of diversity. Personal data provided by applicants will be used for recruitment and other employment-related purposes. Best Global Universities Rankings #54 (U.S.News & World Report 2025-2026); World University Rankings #73 (THE 2026); #1 in the World’s Most International Universities (THE 2024, 2025 & 2026); Young University Rankings #4 (THE 2024); Asia University Rankings #16 (THE 2025) and #7 (QS 2026)

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. This project focuses on federated causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy causal analysis across distributed datasets while preserving privacy. The successful candidate will be responsible for the end-to-end investigation of novel federated learning strategies for causal inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real-world datasets. The core responsibility is to build and validate federated causal inference algorithms through simulations and live demonstrations. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Derivation of novel performance metrics for federated causal inference algorithms. Analysis of causal inference models in federated settings using synthetic and real-world datasets. Design and development of novel federated causal inference algorithms and associated software APIs. Validation of algorithms via simulations and live demonstrations. Job Requirements A Master's degree or higher in Computer Engineering, Computer Science, Data Science, Statistics, or equivalent. Strong theoretical background in statistics and machine learning. Knowledge of the basics of federated learning and causal inference is highly encouraged. Proven track record in research and development of machine learning algorithms. Proficiency in algorithm development using Python and ML frameworks such as PyTorch or TensorFlow. Key Competencies Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Able to build and maintain strong working relationships with people within and external to the university. Self-directed learner who believes in continuous learning and development. Proficient in technical writing and presentation. Possess strong analytical and critical thinking skills.