Senior Research Officer

About the role and project

The postdoctoral researcher (Senior Research Officer) will be integral to the ambitious EyeWarn project, the largest-scale study of its kind, aimed at detecting fatigue and cognitive strain across diverse sectors of UK society, with a particular focus on high-risk occupations. EyeWarn is a three-year initiative led by The University of Essex, and Solvemed, an AI-med-tech company (Cambridge, UK), in collaboration with the University of Oxford and Stanford University. This groundbreaking project leverages AI to provide transformative insights into fatigue monitoring and its societal impact.

Duties of the role

• As a key member of the EyeWarn team, the candidate will apply cutting-edge and custom-designed computer vision and deep learning models to analyse vast video datasets, focusing on extracting robust markers of fatigue and cognitive strain. Responsibilities include performing advanced signal processing on time-series data, analysing pupillometry and eye movement metrics, and optimizing measurement techniques to improve the detection and assessment of fatigue markers.
• The candidate will work closely with Solvemed’s multidisciplinary R&D team and leading scientists from Oxford and Stanford, contributing to the development and refinement of machine learning algorithms that enhance the precision and reliability of the extracted metrics. This role combines AI innovation with practical applications, requiring a deep focus on eye-tracking metrics, bio-pattern analysis, and the creation of AI-driven solutions for indirect neuromonitoring. Through this work, the candidate will play a pivotal role in shaping the future of fatigue detection and cognitive health monitoring at a societal scale.
• Development and Implementation of Advanced Analytics: 1) Designing, implementing, and documenting Artificial Intelligence algorithms for deep learning, computer vision, and signal processing in the context of neuromonitoring. 2) Developing, testing, and refining imaging analytics pipelines to extract key metrics from video and time-series data, particularly related to pupillometry, eye movement, and fatigue detection.
• Machine Learning and Data Processing: 1) Training, retraining, and optimizing deep learning models, including data preparation, augmentation, and integration of additional datasets for model improvement. 2) Running and managing deep learning workflows on both local devices and cloud-based environments (e.g., AWS, GCP), and working effectively with model outputs to derive actionable insights.
• Data Analysis and Signal Processing: 1) Performing time-series processing and statistical analysis to extract bio-patterns and markers of cognitive strain and fatigue. 2) Performing time-series processing and statistical analysis to extract bio-patterns and markers of cognitive strain and fatigue.
• Collaboration and Research: 1) Working closely with Solvemed’s R&D team and scientists from the University of Oxford and Stanford University to advance the project’s goals. 2) Engaging with other professionals to align model development and analytical pipelines with broader scientific and clinical objectives.
• Tool and Workflow Development: 1) Creating and maintaining tools for monitoring data flow, novel data visualization, and user-friendly interfaces for the research platform. 2) Creating endpoints for accessing library functionality as service. 3) Embracing modern AI tools, including large language models (LLMs), to accelerate and enhance workflows and boost team productivity.

Skills and qualifications required

The successful candidate should posses a PhD in Computer Science, Artificial Intelligence, Mathematics, Physics, Data Science, Bioengineering or related discipline. You will have the ability and willingness to complement and enhance the research project/department/school’s education and research strengths and areas of planned development. Strong communication skills, both written and verbal are also essential for the post.

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