Professor Kate Robson Brown, Director
Kate became Director of the Jean Golding Institute in August 2017 and leads the team in providing a strategic direction for the Institute. She is Professor of Biological Anthropology and affiliated to both the School of Arts and the School of Civil, Aerospace and Mechanical Engineering at the University of Bristol. Kate joined the University of Bristol in 1997 following her first degree in Archaeology and Anthropology and PhD in phylogenetics at the University of Cambridge. Her research focuses on how the hard tissues of the human body hold a signature of life history. She explores the microstructure of bone, dentition and soft tissues; innovating methodologies for the data capture, analysis and interpretation of material characterisation to address a range of challenges posed by anthropological, biomechanical, forensic, developmental and evolutionary applications.
Patricia Holley MSc, Manager
Patty is the Manager of the Institute and her main role is to develop, plan and support a range of activities in order to create avenues for multidisciplinary research, links with business, partnerships and community engagement. Patty has been working in Research Management and Administration for the past ten years and previously worked as a project manager for SPHERE, a flagship interdisciplinary collaboration at the University of Bristol. This EPSRC-funded project is a £12M collaboration developing a sensor platform to support healthcare at home. She also worked in the Research and Enterprise Development (RED) department as a Research Development Associate promoting multidisciplinary, cross-sector collaborations. She has a Masters in Biology from Wake Forest University where she studied the foraging behaviour of Hawaiian albatrosses.
Natalie Thurlby, Data Science Specialist
Natalie joined the Jean Golding Institute as the Data Science Specialist in August 2018. Her main responsibilities at the institute include helping researchers at the university with data science queries through the Ask JGI service, and carrying out data science projects. After completing her first degree in Maths and Physics at the University of Manchester, she moved to the University of Bristol to study for her PhD in Computational Biology, which she's currently finishing. Her research focuses on predicting human phenotype and protein function using clustering and outlier detection methodologies.
Liz Green, Research Institute Coordinator
Liz joined the team in August 2017 and her role in the Jean Golding Institute includes managing the website, social media and other communications, organising events and coordinating the administrative aspects of the Institute. She has a background in health, clinical research and research administration and worked as a nurse for many years. Liz is currently undertaking a Masters in Nutrition, Physical Activity and Public Health at the University of Bristol and during her studies is job-sharing with Rachel. Liz's working days are Mondays and Wednesdays.
Rachel Prior, Research Institute Coordinator
Rachel joined the team in September 2018 and shares the role of JGI Coordinator with Liz, working Tuesdays, Thursdays and Friday mornings. Rachel has a background in events and administration, and has previously worked with the Who Do You Think You Are? Live show held at London Olympia. She has a Masters in Comparative Literature and Culture from the University of Bristol where she specialised in contemporary Japan and digital culture.
Robert Arbon, Data Science Specialist
Robert works at the Jean Golding Institute as a Data Science specialist alongside Natalie. Robert is currently finishing a PhD in computational chemistry, producing hidden Markov models of proteins to explain their behaviour. As well as charts (visual display) Robert has also produced audio displays to convey model information. Robert previously worked in environmental and economic consultancy focusing on developing countries for donors such as the World Bank. Research interests include meta-research and borrowing machine learning and statistical methods from one discipline and applying them to another.