Paderborn University

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 primary responsibility of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key 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: i. Develop, train, and optimise deep learning models for object detection, classification, and segmentation using real-world datasets. ii. Design and implement software modules to integrate the models into a working system prototype. iii. Perform data annotation. iv. Conduct experiments, analyse results, and iterate models for improved accuracy and efficiency. v. Prepare project documentation, technical reports, and academic publications. vi. Collaborate with industry partners and contribute to technology transfer efforts. Job Requirements Possess strong technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models Hold at least a Bachelor’s degree in Computer Science, Electrical/Electronic/Software Engineering, or a related field. A Master’s or PhD degree in relevant areas will be advantageous. Familiarity with the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D projects Key Competencies Able to build and maintain strong working relationships with team members, stakeholders, and external partners Self-motivated and committed to continuous learning and improvement Proficient in technical writing & presentation, research reporting, and academic publication Possess strong analytical, problem-solving, and critical thinking skills Demonstrate initiative and ownership in carrying out tasks independently

The Health and Social Sciences Cluster at SIT has been at the forefront of allied health education and research, offering a suite of allied health programmes and two nursing programmes. As a young university, we foster an academic environment that seamlessly integrates teaching, applied research and clinical practice. We offer competitive remuneration, generous employment benefits, access to funding to undertake clinical research, and opportunities to inspire and nurture the next generation of skilled allied health and nursing professionals. About the Positions We currently have positions available from Assistant Professor to Full Professor, for the following disciplines: Diagnostic Radiography Dietetics Nursing Occupational Therapy Physiotherapy Speech and Language Therapy Applicants should meet all the criteria below: (a) an earned PhD in the respective healthcare discipline from a reputable university; (b) excellent research track record; (c) deep clinical experience in the respective healthcare discipline. We will prioritise collegial and team-spirited candidates with an earned PhD in a related discipline from a reputable university, plus relevant work experience or experience of industry-linked applied research projects. Applications will be accepted until the positions are filled. All applications must be submitted electronically via the "Apply Now" button below. 

Liverpool John Moores University (LJMU) is a distinctive, unique institution, rooted in the Liverpool City Region and with a global presence. Our students and staff, past, present, and future, are the beating heart of our city and can be found in every corner of every industry and community. We couldn’t exist anywhere else and have shaped the city in which we belong. Working with the people of Liverpool to improve lives and support communities is at the heart of why we were founded and why we exist today. Supporting the delivery of Strength and Conditioning (S&C) services to university athletes and other partners. To develop, manage and lead on the delivery of an effective strength & conditioning programme for the LJMU Performance Sport Programme. This will include designing, delivering and evaluating strength and conditioning sessions for the LJMU Performance Sport athletes based in Liverpool by developing, implementing and evaluating strength and conditioning programmes that reflect scientific principles as they relate to adaptation, periodisation, peaking, tapering, injury prevention, rehabilitation, recovery and athlete screening/assessment. The role will also include management of S&C practitioners that are responsible for S&C delivery to TASS scholars and externally contracted athletes. In return, we offer an excellent benefits package including generous annual leave entitlement, pension scheme, induction and development support as well as family-friendly policies. This is an exciting time to join the university as we deliver the LJMU Strategy 2030 and its vision of LJMU as an inclusive civic university transforming lives and futures, by placing students at the heart of everything we do. If you feel that this is the role you have been looking for and your skills and experience can make a real difference at LJMU, we look forward to hearing from you. LJMU is an equal opportunities employer and welcomes applicants from all backgrounds and communities irrespective of age, transgender status, disability, gender, sexual orientation, ethnicity and religion or belief. All our appointments are made on merit. Please note all of our vacancies will be closed to applications at midnight on the advertised closing date, unless otherwise stated.