Research Associate in Algorithm Development and Data Science

Position: We are seeking to recruit a Research Associate in Data Science to join our multi-disciplinary team. If you are excited by interdisciplinary collaboration, cutting-edge technology, and real-world impact, this is your chance to shape the future of offshore renewables.

This role focuses on developing novel data processing techniques to automate detection, classification, and sensor fusion for monitoring offshore renewable energy. Large datasets collected across active and passive acoustics, sometimes supported by camera imagery, require development of robust and reliable algorithms to automate filtering, target detection, tracking and classification. Evaluation of algorithm performance across environmental conditions is needed to quantify uncertainty and allow confidence in decision making. Sensor fusion can also be used to mitigate the limitations of different instruments, or to allow combination of detection e.g., vocalising cetaceans from passive acoustics with concurrent measures of prey using active acoustics.

As new sensors and technologies are developed, e.g., broadband active acoustics or multi-frequency imaging sonar, a robust evaluation of instrument performance in controlled conditions is also required. With the vast amounts of data collected through these various sensors, machine learning and advanced algorithms can unlock new ecological insights.

Responsibilities: The post holders will lead development of algorithms for data processing and analysis, with a focus on imaging sonar data, and future directions including multifrequency echosounder and broadband passive acoustic data. You will explore and demonstrate opportunities for sensor fusion and design structured trials to evaluate and characterise the performance of new sensors. You will explore opportunities to contribute to wider data processing ranging from radar remote sensing, to aerial drone measurements of surface currents and marine plastic litter.

Qualifications, Experience and Skills: The suitable candidates will have the knowledge, skills and experience associated with a first degree, together with a PhD or equivalent professional qualification/ at least 4 years appropriate professional experience. You will have the developing ability to prepare research proposals, to conduct individual research work and to disseminate results. You will have excellent analytical, programming or data science/computer science experience, with experience in managing and processing large datasets. An interest in machine learning/ deep learning and applicability to marine sensing is required as well as a passion for transforming complex datasets into actionable ecological insights.

Experience of academic teaching would be advantageous.

Benefits of working for us: 

• 45 days annual leave per year (pro rata for part-time staff)
• Local Government Pension Scheme (Highland Council)
• 10% Membership Discount at Highlife Highland 
• Occupational sick pay scheme and family friendly leave provisions
• Staff Support and Employee Assistance Programmes
• Employment Benefits Scheme including lifestyle savings and Cycle to Work Scheme

To Apply: For a full job description and an application form, download the pack at: Staff - Vacancies (uhi.ac.uk) or email recruitment.nwh@uhi.ac.uk

Please include your CV with your application.

• Job description
• Guidance Notes for Candidates
• Personal Details Form
• Application form

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