Technical Lead - Computer Vision and Machine Learning

Description of Post

ATU Sligo has recently secured funding from Enterprise Ireland to commercialize exciting novel research in the application of Computer Vision and Machine Learning in emulsion manufacturing. The project titled “Inline Characterization Of Multiphase Systems” (ICOMS) focuses on automating the characterization and quality prediction of emulsion-based products through image analysis and machine learning models. A US patent is filed and published on this work by the inventor team. The primary objective of the project is to develop a Software as a Service (SaaS) for the published ICOMS technology by extending its functionality further as per the market needs and to establish a campus spin-out company on completion of the current 2-year contract period.

Essential Qualifications

• PhD (minimum), Postdoc (preferred) in Applied Mathematics and Statistics, Computer Science or an Engineering discipline relevant to the expertise outlined below; minimum 5 years’ research experience post PhD in Industry or Academia.
• Deep and diverse knowledge of applied mathematics and statistics e.g., Linear Algebra; probability theory and statistical modelling.
• Deep and diverse knowledge in Computer Vision both in theory and practice; Expert knowledge of Image processing, segmentation and analysis algorithms; video processing and analysis software tools and techniques.
• Deep and diverse knowledge of State-of-the-art Machine Learning (ML) and Deep Learning (DL) models, their concepts including unsupervised and supervised classification algorithms.

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