University of Helsinki

Location Docklands Campus Salary £39,824 to £45,281 per annum inclusive of London Weighting Post Type Full Time Post Type Permanent Closing Date Sunday 18 January 2026 Interview Date Friday 30 January 2026 Reference 103S2025 University of East London We’re the University of East London (UEL), founded in 1898 and proud to change lives through education. Our goal is to advance industry 5.0, careers-first education and provide a clear path to the jobs and opportunities of the future. We’re committed to driving diversity in the 5.0 talent pipeline, working in partnership to promote talent wherever it is found and creating a sustainable, inclusive and green future. But we can’t achieve this alone. We need forward-thinking, innovative and curious individuals to join our community and help shape what comes next. At UEL, you’ll work with colleagues who share a passion for creativity, technology and positive change, in an inclusive and welcoming environment that is constantly evolving. About the School / Service The Technical Services team supporting the Schools of Arts & Creative Industries (ACI) and Architecture, Computing & Engineering (ACE) is a crucial part of the University of East London’s infrastructure. Working as a unified and collaborative technical team, we support students and staff across both Schools by providing specialist expertise, facilities and resources that enable high-quality learning, teaching, research and public-facing activity. Our technicians work collectively across a wide range of disciplines and facilities, supporting practical teaching, experimentation, exhibitions and research activity. The team operates with shared goals, common standards and a strong culture of collaboration, ensuring consistency, resilience and innovation across ACI and ACE. This is an exciting time to join Technical Services at UEL as we continue to invest in our people, spaces and technologies. We are committed to professionalising technical roles, encouraging cross-team working and building an inclusive, forward-looking technical community that is closely aligned with curriculum development and industry practice. About the Job We are seeking an experienced and motivated Technical Group Leader to provide leadership across our Digital Fabrication Labs (dfUEL) Print and Fashion technical provision. In this role, you will lead a team of skilled technicians supporting students, academic staff and researchers across ACI and ACE. You will oversee specialist workshops, equipment and digital manufacturing resources, ensuring safe, effective and innovative technical support that enhances learning, teaching and research. This is a hands-on leadership role for someone passionate about technical innovation, collaboration and enabling creative practice. Key responsibilities include: Leading, supervising and developing a multidisciplinary technical team across Digital Fabrication, Print and Fashion. Managing specialist workshops, labs and equipment supporting digital manufacturing, fabrication and fashion technologies Supporting curriculum delivery, research and exhibitions through expert technical advice, demonstrations and workshops Ensuring safe, compliant and well-maintained technical environments, embedding health and safety best practice Working closely with academic colleagues and professional services to align technical provision with teaching and research needs Contributing to the continuous development of technical services, processes and future investment planning Supporting the day-to-day operations of Digital Fabrication including the ABB robotic arm and related software including Grasshopper. About You You will be a confident and collaborative technical leader with experience in digital fabrication, manufacturing, fashion technology or related creative and technical disciplines. You may have deep expertise in one area, combined with the curiosity and willingness to work across a broad technical portfolio. You will bring: Experience leading or supervising a technical team within higher education, industry or a creative/technical environment Strong technical expertise in at least one relevant area (e.g. digital fabrication, CNC, robotics, fashion technology, model making or applied materials) A genuine passion for supporting students and staff in practical, hands-on learning environments Excellent communication and organisational skills, with the ability to work effectively across disciplines and departments A proactive approach to technical innovation, sustainability and continuous improvement A strong commitment to Equality, Diversity and Inclusion and to working in line with UEL’s values Benefits Package At UEL, we believe that a great role is about more than just a salary. It’s about the complete package, including our outstanding work environment and inclusive culture. We offer a genuinely competitive salary, dependent on experience (DOE), alongside a comprehensive benefits package. You can explore our full benefits package here:  https://uel.ac.uk/benefits-professional-services-positions Equal Opportunities As an inclusive, equal-opportunities employer, our Stonewall membership and Athena Swan awards reflect our ongoing commitment to Equality, Diversity and Inclusion. We’re proud of the progress we’ve made and honest that there is more to do. We are determined to keep moving forward so everyone at UEL can thrive. So, if you’re ready to lead technical innovation, support creative and digital education, and make a real impact at the University of East London, we’d love to hear from you. Apply today. Please note that this advert may close earlier than the stated deadline if we receive a high volume of applications. Early applications are encouraged. Further Details Job Description & Person Specification To contact the recruitment team please phone +44 20 8223 3000 x 4600 or e-mail jobs@uel.ac.uk CVs without a completed application form will not be accepted. At UEL we are committed to working together to build a community which values diversity in both our staff and student populations, is representative and inclusive, enabling all to progress and thrive.

The University of Vienna is a community of over 10,000 individuals, including approximately 7,500 academic staff members, who passionately pursue answers to the profound questions that shape our future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their passion and determination? We are currently seeking a/an University assistant predoctoral 34 Faculty of Law Startdate: 01.02.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.01.2030 Reference no.: 5092 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere of influence: We are a highly dedicated team working intensively in the area of teaching and researching Austrian and international civil procedure. We offer flexible working hours, possibilities of further and continuing education, a pleasant working atmosphere and an adequate initial salary. As a university assistant prae doc, you will complement the research team around Univ.-Prof. Dr. Dr.h.c. Paul Oberhammer. The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration. Your future tasks: You actively participate in research, teaching & administration, which means: You are involved in research projects and scientific studies, pulbications and the organisation of conferences and symposiums. We expect you to finalize your dissertation agreement within 12-18 months. You work on your dissertation and its completion. You hold courses independently within the scope of the provisions of the collective bargaining agreement. You take on administrative tasks in research, teaching and administration. In particular, you will contribute to the scientific work of the research center "Institute for Notarial Law". This is part of your personality: Completed Master's degree or Diploma in the field of law University studies completed with good success, particularly in the field of civil procedure, proven by results of examinations (presentation of transcript of records and grades mandatory for application), therefore excellent knowledge of Austrian procedural law Knowledge of international arbitration law Knowledge of university processes and structures Basic experience and interest in academic writing and with research methods Excellent command of written and spoken English (C1 Level) High ability to express yourself both orally and in writing Didactic competences IT user skills You should be a team player with high social skills. 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 all: We welcome every additional/new personality to the team! It is that easy to apply: With your scientific curriculum vitae With your letter of motivation With your summary of reserach interests / ideas for a prospective doctoral project proposal With your list of publications (if available) With evidence of teaching experience (if available) With degree certificates With your Master Degree / Diploma Via our  job portal / Apply now - button If you have any questions, please contact: Petra Peirleitner petra.peirleitner@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: 01/15/2026

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.  The Research Engineer will play a key role in automated wildlife identification and classification from trap camera images using cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities Participate in and manage the research project together with the PI, Co-PI, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: Develop, train, and optimise deep learning models for wildlife species identification, classification, and segmentation using real-world datasets. Design and implement software modules to integrate the models into a working system prototype. Perform data annotation. Conduct experiments, analyse results, and iterate models for improved accuracy and efficiency. Prepare project documentation, technical reports, and academic publications. Collaborate with industry partners and contribute to technology transfer efforts. Support the design of simple web interfaces or dashboards to visualise CV model outputs, working alongside developers when needed. Contribute to system integration by applying familiarity with backend/frontend workflows, ensuring CV models can be accessed through user-facing applications. Assist in deployment of CV solutions on cloud or edge platforms with basic interface support for end-users. The candidate is to liaise and communicate with any internal or external stakeholders to ensure project deliverables are met and to perform any other adhoc duties assigned by Supervisor.   Technical Requirements: Possess strong technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow, Keras) Computer vision models for object detection and classification (e.g., YOLO, R-CNN variants, EfficientNet, ResNet, U-Net) Image processing and computer vision techniques  Python programming and relevant libraries (e.g., OpenCV, NumPy, scikit-learn, Pandas, Matplotlib) Experience with dataset preparation, model training, and performance evaluation Candidates with strong computer vision expertise and proven success in 1-2 substantial CV projects are welcome to apply regardless of domain-specific experience Familiarity with Web/Full-Stack Development: Basic understanding of frontend frameworks (e.g., React, Angular, or Vue.js) Eposure to backend development (e.g., Flask, Django, Node.js) Awareness of RESTful APIs and microservices architecture. General knowledge of database systems (SQL/NoSQL). Experience with cloud platforms (AWS, GCP, Azure) for deployment and scaling Educational Requirements: Hold at least a Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological datasets or wildlife imagery Familiarity with data annotation tools and practices for large-scale datasets Knowledge of model deployment and optimization (e.g., ONNX, TensorRT, model quantization) Experience with edge computing or embedded systems (e.g., NVIDIA Jetson, Raspberry Pi) Background in real-time processing and GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer vision challenges) Experience with version control (Git) and collaborative development practices