Carl von Ossietzky Universitat Oldenburg

About us ​​King’s Centre for International Education and Languages a new, cross-cutting Centre designed to widen the educational reach of King’s. It brings together three existing areas: King’s Foundations, Summer Programmes, and King’s Language Centre. This brings together international pathway provision, pre sessional programmes, pre-UG summer courses, UG summer modules, UG language modules, bespoke language programmes for the community and our partners and academic skills provision for all King’s students. ​Each of these areas are well established, respected and recognised within and beyond the King’s community. The Centre is focused on enabling collaboration between the three departments to further advance our work in promoting educational excellence and supporting and enhancing the student experience. The Centre has expertise in International Education and makes a significant contribution to the rich and diverse make-up of the King’s student body. About the role The Learning Technology Officer will support the implementation of Digital Education initiatives at the Centre for International Education and Languages (CIEL), which includes King’s Language Centre, King’s Foundations, and King’s Summer. CIEL comprises around 250 academic and professional services staff and teaches over 12,000 students each year. This role provides practical, hands-on support for the use of digital learning technologies across the Centre. The postholder will assist with the setup and design of KEATS (Moodle VLE), contribute to the creation and maintenance of digital learning materials, and support staff and students in the effective use of digital tools such as Turnitin and Kaltura. They will also contribute to training delivery, process improvement, and the evaluation of digital education practices. The successful candidate will play a key role in fostering an inclusive, forward-thinking digital learning environment that enhances both student and staff experiences through consistent, accessible, and engaging use of technology. This is a full time, and you will be offered an indefinite contract. About you To be successful in this role, we are looking for candidates to have the following skills and experience:  Essential criteria Educated to degree level or equivalent experience. Strong technical skills and experience providing DE support in an education context. Strong knowledge of current and emerging digital education tools and technologies. Experience managing and supporting Virtual Learning Environments (VLEs) and learning technologies. Expertise in developing training materials and conducting Digital Education workshops. Excellent task management and problem-solving skills, with the ability to manage multiple projects and meet deadlines. Excellent communication and interpersonal skills, with the ability to collaborate effectively with diverse stakeholders. Knowledge of accessibility standards and inclusive teaching practices. Desirable criteria Certified membership of relevant professional bodies (e.g., CMALT). Experience of working in higher education contexts. Working knowledge of video editing software and other media tools. Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's. As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible. To find out how our managers will review your application, please take a look at our ‘How we Recruit’ pages. This post is subject to Disclosure and Barring Service clearances. Grade and Salary: £38,482 – £43,249 per annum including London Weighting Allowance Job ID: 131505 Close Date: 19-Jan-2026 Contact Person: Mr Chris Green Contact Details: Christopher.g.green@kcl.ac.uk

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

Description Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is looking for passionate and highly motivated Teaching Faculty in the field of Artificial Intelligence. The successful candidates will be responsible for delivering high-quality instruction, mentoring students and contribute to curriculum development.  Faculty members will also have the opportunity to collaborate with leading AI researchers, work on cutting-edge projects, and contribute to the university's growth as a hub for AI excellence. About the Course – Artificial Intelligence in Action The Master in Applied Artificial Intelligence (MAAI) program is designed to address the critical skills gap in Artificial Intelligence applications within industry, both in the UAE and globally. Combining theoretical knowledge with practical, hands-on experience, the program equips students with advanced skills for adapting and implementing Artificial Intelligence technologies in industry, research, and government sectors. Aligned with Abu Dhabi’s knowledge economy vision, the Master in Applied Artificial Intelligence program educates future leaders in cutting-edge Artificial Intelligence applications, supporting national Artificial Intelligence strategies and economic and societal development in the UAE. This industry-focused, project-based curriculum emphasizes development of applied and entrepreneurial skills, preparing graduates to create Artificial Intelligence innovations and societal, economic and environmental impact. About MBZUAI – A Global Leader in AI Research and Education MBZUAI is the world’s first university dedicated exclusively to AI and is rapidly emerging as a global leader in the field. Since its establishment in 2019, MBZUAI has grown into a top-ranked AI institution, currently hosting 80+ world-class faculty and 330+ graduate students and ranking among the top 10 AI universities worldwide. With ambitious plans to expand from 8 to over 20 AI departments and grow its faculty from 84 to 300 by 2030, MBZUAI is on a fast-track growth trajectory. By integrating academia, industry, and government collaboration, we are driving AI innovation to address real-world challenges in healthcare, sustainability, and beyond. Why Join MBZUAI? Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions Funding: MBZUAI empowers researchers with resources and academic freedom, fostering groundbreaking AI advancements in an environment of innovation and independent inquiry. Exceptional Benefits: Comprehensive health & life insurance Relocation support for international faculty State-of-the-Art Research Facilities: Cutting-edge AI labs and high-performance computing Live in Abu Dhabi: World’s safest city, year-round sunshine, rich culture, and modern amenities Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers Description of the Role: This appointment involves delivering courses for a master’s in applied artificial intelligence program for mid-to senior level career professionals. It requires strong industry experience, and familiarity with the business landscape in the  and with that requires industry experience and the knowledge of the business environment in the United Arab Emirates is considered an advantage. The faculty shall deliver world-class education and student experience with innovative approaches to teaching and learning. The faculty will engage with industry to discover innovative industry projects, continuously develop the rigor and relevance of the course curriculum, and support students in their research projects. The faculty will supervise student internships and industry research projects and liaise with industry partners for the achievement of the program learning outcomes. Industry engagement further involves sourcing experts and qualified guest lecturers for the program. The faculty shall maintain an appropriate scholarly or professional development activity and to keep up to date with developments in the field as necessary to carry out the duties of the position. (S)He shall contribute to the overall work of the university by representing the institution and faculty on appropriate committees and groups. The faculty shall follow scientific developments in the field and participate in societal interaction and international cooperation in his/her field.  Qualifications Applicants preferably have a PhD in computer science or in a closely related area prior to the start of the appointment and should have demonstrated excellence in conducting innovative and impactful research and applying advanced technologies in solving real business challenges, and an interest in mentoring graduate students. In exceptional cases, candidates without a PhD may be considered if they possess outstanding experience in AI application, education, or industry practice. Application Instructions The apply for this position, please submit the following items: Cover Letter Curriculum Vitae A statement of teaching philosophy and experience Reference letters from three contactable referees MBZUAI's mission includes fostering a diverse academic community. MBZUAI is an equal opportunity employer. The university actively recruits faculty from around the world, aiming to create an international and inclusive environment that reflects a wide range of cultures and perspectives.  Be a part of AI’s future – apply today at MBZUAI! #MBZUAI #careeropportunities #AI Equal Employment Opportunity Statement Mohamed bin Zayed University of Artificial Intelligence shall abide by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, national origin, protected veteran status or disability.