Rob Brisk, MBBCh, PhD

Rob Brisk, MBBCh, PhD has a diverse work experience spanning various roles and industries. Currently, they are the Chief Scientific Officer at Eolas Medical, where they lead data science efforts to organize medical information and improve healthcare. Prior to this, Rob worked at NVIDIA, where they managed global partnerships with pharmaceutical companies, academic institutions, and software vendors as the Global Lead of Life Sciences Alliances. Rob also served as the DevRel/Alliance Manager in Healthcare at NVIDIA.

Before joining NVIDIA, Rob worked at the Department of Health Northern Ireland as a Scientific Advisor, where they developed a digital twin model for healthcare resources during the initial phase of the pandemic. Rob was responsible for informing national service planning and provisioning of key equipment in the health and social care system.

Rob has also held roles at Southern Health and Social Care Trust, where they worked as a Clinical Research Fellow and a Specialty Doctor in Cardiology. Additionally, they served as an Advanced Life Support Instructor at the Resuscitation Council (UK) and began their medical career as a Medical Doctor in the NHS. Overall, Rob Brisk's work experience reflects their expertise in healthcare, data science, partnerships, and clinical research.

Rob Brisk, MBBCh, PhD completed their Bachelor of Medicine, Bachelor of Surgery (M.B.B.S.) from the University of Wales between 2004 and 2010. Later, in 2013, they pursued further education at the Royal College of Physicians of London, where they obtained their MRCP degree in Medicine. Additionally, they completed their PhD in Computer Science at Ulster University, commencing in 2018 and expected to finish in 2022. Throughout their academic journey, Rob Brisk also obtained several certifications in machine learning and deep neural networks from Coursera, including "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," "Convolutional Neural Networks," "Structuring Machine Learning Projects," "Neural Networks and Deep Learning," and "Machine Learning."