Research Assistant in AI-based Image Analysis

About the role

Department: Research / DeepCamera No. Of Positions: 1 Reporting Line: Research Team Leader Contract Type: An initial one-year fixed term employment contract will be offered with the possibility for renewal. Full Time basis. Duration of project : 36 months (September 2026 - August 2029) Location: Nicosia, Cyprus Indicative Annual Gross Salary Range: €18,000 - €23,000 The salary will be determined based on qualifications, experience, and suitability for the role. Preferred Start Date: July 2026, or as soon as possible. Application Deadline: 19 th of June 2026. Applications will be reviewed on a rolling basis. About the project / position: The successful candidate will work in the area of AI-based underwater image analysis and marine species detection. Marine biodiversity monitoring currently relies on large volumes of underwater video footage that must be manually analysed, a process that is time-consuming and prone to variability. Advances in artificial intelligence and computer vision provide the opportunity to automate species detection and classification, significantly improving efficiency and consistency in marine ecological assessments. In this role, the successful candidate will develop, train, and validate deep learning models for automated detection and classification of marine species from underwater imagery and video datasets. The position is part of the EU-funded ATLANTIS project (I3-ERDF), developing underwater technologies for marine monitoring and sustainable blue-economy applications. The successful candidates will have the opportunity to conduct fundamental and/or applied research in the aforementioned areas. Where applicable, candidates may also participate in the preparation of project reports and deliverables, research proposals for funding, software development, and travel abroad for dissemination activities. Furthermore, successful candidates will be encouraged to publish/present their research results in prestigious international conferences and journals. Key Responsibilities: Perform data curation, preprocessing, and quality control of underwater imagery and video datasets, in collaboration with marine experts Design, train, and evaluate deep learning models for automated detection and classification of marine species Develop computer vision pipelines for video processing and model inference Evaluate model performance using quantitative metrics Contribute to the integration of AI-based detection models into operational biodiversity monitoring workflows and data analysis pipelines Collaborate with project partners and contribute to the preparation of deliverables, technical reports, and dissemination materials Contribute to other activities of the research group and the Centre Skills and Competencies The ideal candidate will be: Ability to work independently, meet deadlines, and collaborate effectively within an interdisciplinary team Strong organisational and problem-solving skills Self-motivated with the ability to take initiative and work independently. Strong organizational, communication, presentation, and negotiation skills, having the ability to deal confidently and politely with enquiries. Very good analytical skills coupled with attention to detail. Dynamic, adaptable, hands-on and results driven. A team player with an ability to work independently and under pressure. High levels of commitment, energy, and drive. Excellent communication and interpersonal skills. Key requirements Essential Requirements M.Sc. / Ph.D. in Computer Vision, Artificial Intelligence, Computer Science, Data Science, Machine Learning, Robotics, or a closely related field , or in related area. 3 years of relevant experience required Demonstrated experience in applied research in artificial intelligence or computer vision Experience in experimental design, model training, and quantitative evaluation of machine learning systems Evidence of scientific writing and dissemination (e.g. peer-reviewed journal publications, conference presentations) Strong programming skills in Python, with experience using deep learning frameworks (e.g. PyTorch or TensorFlow) Experience in computer vision and image or video analysis Language requirements: Excellent written and oral English-language skills will be required. For non-EU applicants a work permit will be required Desirable Qualifications The following will be considered an advantage: Experience with object detection or image segmentation models (e.g. YOLO, Mask R-CNN, Detectron2, etc.) Experience working with large image or video datasets and annotation tools (e.g. CVAT) Familiarity with Linux-based computing environments and version control systems (e.g. Git) Experience with data augmentation, transfer learning, or domain adaptation techniques Prior experience with environmental monitoring, marine datasets, or remote sensing imagery Previous research experience and high impact research publications on relevant topics (a requirement for PhD holders/an advantage for no

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