Pomorski Uniwersytet Medyczny w Szczecinie
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Research Engineer (Computer Vision - Wildlife Species) - SH1
Singapore Institute of Technology (SIT)
Singapore
Singapore Institute of Technology (SIT)
Singapore
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
Salary
Competitive
Posted
10 Apr 2026
Research Engineer/Research Fellow (LLM/VLM, Media Comparison, AI-Assisted Explainability) - IM
Singapore Institute of Technology (SIT)
Singapore
Singapore Institute of Technology (SIT)
Singapore
As Singapore’s University for Industry, SIT works closely with industry partners 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 position is to deliver on a research project to develop an End-to-end misinformation and disinformation protection, awareness and mitigation pipeline. We will be recruiting a research engineers or fellows, as part of a wider project, to conduct research on: LLM/VLM, media comparison, AI-assisted explainability. The need is for a real-time system, so efficient coding is important. Key Responsibilities: Participate in and manage the research project with Principal Investigator (PI) Ian McLoughlin, Co-PI Tong Rong and the research team members to ensure all project deliverables are met. Undertake research within your domain, including keeping track of state-of-the-art work. Develop the code, evaluate and test. Write academic publications. Deliver solution-ready demonstration code. Interact well within the team and the customers. Be self-directed to fulfil the project requirements. Job Requirements: Competence in working with languages such as C along with Python-based coding and AI development. Have a degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image processing is required. Ability to effectively and efficiently utilise industry-standard Linux-based computers for AI. Experience of authoring good quality academic publications. Manage undergraduate research assistants (if appropriate). Liaise with customers and collaborators in A*STAR and NTU, as well as collaborators in the UK and China. Key Competencies: A self-directed worker who believes in continuous learning and development Proficient in academic writing Possess good critical thinking skills Show strong initiative and take ownership of work Interest in AI, machine learning, image/audio processing
Salary
Competitive
Posted
10 Apr 2026
Research Assistant
Hong Kong Baptist University
Hong Kong
Hong Kong Baptist University
Hong Kong
Job Description LIFE SCIENCE IMAGING CENTER Research Assistant (25260649) The research assistant is expected to contribute/support cognitive neuroscience research on interdisciplinary projects, duties include literature review, data collection, data analysis and drafting manuscript. The appointee is expected to work with researchers at Life Science Imaging Center (LSIC). LSIC is a central research facility (https://lsic.hkbu.edu.hk/) built to support and promote cutting-edge neurocognitive studies across disciplines at HKBU. LSIC is equipped with a high-performance 3T Magnetic Resonance Imaging (MRI) system that enables researchers to explore the structure and function of human brain. A high-performing computing server has been set up to support MRI data analysis. Responsibilities: Manage MRI slot booking and the subject booking system, do data preprocessing, help with task programming, and manage devices (EEG/TMS/biopac/eyetracking/fNIRS); Help with administrative duties, such as organising workshops, inviting speakers, reimbursement; and Perform any other duties as assigned by the supervisor. Requirements: A bachelor’s degree in sciences or other related disciplines (e.g., Psychology, neuroscience); Good analytical, communication and interpersonal skills; Good command of written and spoken English and Chinese (good command of Cantonese is preferred); and Experience with some neuroscience-related equipment (EEG/TMS/biopac/eyetracking/fNIRS) is preferable. The initial appointment will be offered on a fixed-term contract of 12 months commencing as soon as possible. Salary will be commensurate with qualifications and experience. Application Procedure: Applicants are invited to submit their applications to the HKBU e-Recruitment System. Those who are not invited for interview 8 weeks after submission of application may consider their applications unsuccessful. Details of the University’s Personal Information Collection Statement can be found at https://hro.hkbu.edu.hk/en/worklife-at-hkbu/employee-favourable-environment.html#privacy-policy. The University reserves the right not to make an appointment for the post advertised, and the appointment will be made according to the terms and conditions applicable at the time of offer. Review of applications is ongoing until the position is filled.
Salary
Competitive
Posted
10 Apr 2026
Research Assistant (in Spinal Sarcopenia in Older Adults) - ZWH
Singapore Institute of Technology (SIT)
Singapore
Singapore Institute of Technology (SIT)
Singapore
Research Assistant Health and Social Sciences Cluster Singapore Institute of Technology We are seeking a motivated and capable Research Assistant to join an exciting translational research project on spinal sarcopenia in older adults, with a focus on muscle degeneration, senescent progenitors, and regenerative failure. This role offers a unique opportunity to work across clinical research, functional assessment, imaging analysis, and laboratory investigation in a multidisciplinary academic environment. The successful candidate will support a funded research project that aims to generate clinically relevant insights into ageing, muscle health, and spine-related conditions. This is an excellent opportunity for candidates who are passionate about meaningful research and wish to build strong experience in applied human and translational studies. Key Responsibilities Support the Principal Investigator and research team in the implementation and coordination of the project Assist with participant recruitment, scheduling, follow-up, and study administration in accordance with approved ethics protocols Conduct and document functional assessments and study-related data collection Retrieve, organise, and manage imaging data, and assist with image-based analysis Support laboratory workflows such as tissue handling, histology, immunofluorescence, qPCR, ELISA, and related analyses Maintain accurate databases, study records, and project documentation Assist with literature review, data cleaning, preliminary analysis preparation, reporting, and regulatory submissions Coordinate procurement of reagents, consumables, and research-related items Ensure compliance with laboratory safety, biosafety, and institutional research governance requirements Job Requirements Bachelor’s degree in biomedical science, life sciences, physiotherapy, diagnostic radiography, medical laboratory science, or a related discipline Strong interest in translational, musculoskeletal, ageing, or clinical research Experience in clinical research coordination, patient-facing data collection, imaging analysis, or laboratory techniques will be advantageous Familiarity with histology, microscopy, immunofluorescence, molecular assays, or tissue-based workflows is preferred Good written and verbal communication skills Strong organisational skills, attention to detail, and professionalism Proficiency in Microsoft Office; familiarity with ImageJ, SPSS, STATA, or equivalent tools is an advantage Key Attributes Motivated, responsible, and able to work independently Careful and accurate in handling data, samples, and documentation Strong team player who can work effectively with academic, clinical, and student collaborators Willingness to learn and adapt in a dynamic multidisciplinary research environment Why Join Us This role offers valuable exposure to clinically relevant translational research with opportunities to develop experience in human studies, imaging, laboratory science, and multidisciplinary collaboration. The successful candidate will contribute to a meaningful project with real-world healthcare relevance while building a strong foundation for future research or postgraduate opportunities. Contract Type 1-year contract Work Location Singapore Institute of Technology, with project activities at SIT and partner sites as required.
Salary
Competitive
Posted
10 Apr 2026
Tenure-Track Assistant Professor in the Department of Sociology
The University of Hong Kong
Hong Kong
The University of Hong Kong
Hong Kong
Ref.: 534202 Work type: Full-time Department: Department of Sociology (30400) Categories: Professoriate Staff Applications are invited for appointment as Tenure-Track Assistant Professor in the Department of Sociology (Ref.: 534202), to commence in January 2027 or as soon as possible thereafter, on a three-year fixed-term basis with the possibility of renewal and consideration for tenure before the expiry of a second three-year fixed-term contract. The Department of Sociology was founded in 1967 as the first sociology department in Hong Kong. It is based within the Faculty of Social Sciences and encompasses sociology, demography, criminology, and anthropology, fostering an interdisciplinary approach to the study of social issues anywhere in the world. The Department has strong traditions in qualitative research, particularly ethnographic and participatory methods, and has expanded its expertise in quantitative research, social statistics and demography. The 2026 QS World University Ranking rated the Department the 24th among the world’s top 200 universities in the subject of sociology. The Department offers a range of innovative and engaging taught programmes, including undergraduate major/minor programmes in Sociology, Criminology, and Media & Cultural Studies. In addition to research postgraduate degrees, it also offers three taught postgraduate programmes in Sociology, Criminology, and Media, Culture and Creative Cities. Its faculty, research postgraduate students and post-doctoral fellows, are actively engaged in cutting-edge research and excel in producing excellent scholarly research in the social sciences. The Department is also home to the HKU Anthropology Research Network. Information about the Department can be obtained at https://sociology.hku.hk. Applicants should possess a Ph.D. degree in Sociology, Criminology, Anthropology or a related field, and demonstrate a strong commitment to excellence in research, teaching, and academic leadership. Those who are specialised in cybercrime and/or digital harm, with a research background on issues such as surveillance, digital victimology, misinformation, artificial intelligence and crime, and financial crimes (such as online fraud and money laundering) are particularly welcome. A solid research track record in complementing digital methods with theory-driven and empirically grounded work on these topics is an advantage. The appointee is expected to publish research, teach at the undergraduate and postgraduate levels, supervise students at graduate and undergraduate levels, and take on service/administrative responsibilities. A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. At the current rates, salaries tax does not exceed 15% of gross income. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totaling up to 15% of the basic salary. Housing benefits will be provided as applicable. Applicants should apply online at the University’s careers site (https://jobs.hku.hk) and upload (1) a cover letter, (2) an up-to-date CV with the contact information of three referees, (3) graduate transcripts and certificates, (4) one writing sample, (5) a research plan (two pages), (6) a teaching statement (also two pages) and teaching evaluations, and (7) outlines of two proposed undergraduate courses. Review of applications will start as soon as possible and continue until July 1, 2026, or until the post is filled, whichever is earlier.
Salary
Competitive salary
Posted
10 Apr 2026