Jasmyn Gooding is a Research Coordinator in the Faculty of Medicine and Health (FMH) and is completing a PhD in the school of Computer Science (CMP) at UEA. She completed her first degree (MSci) At UEA in Biological Sciences, with a focus on bioinformatics, human health and evolution.

Her research in CMP focuses on applying Deep Learning (DL) to dissect and predict evolutionary signals in the context of genomics.

In FMH her role resolves around coordinating Patient and Public Involvement (PPI) activities across >10 currently funded research projects. Aswell as supporting PPI in the the pre-application phase for >50 projects and fellowships. 

She is the PPIE Lead for the programme grant INfLAIM: Inflammation, nutrition, and the evolution of multiple long term conditions – an AI-based analysis of intersectionality in longitudinal health data.

She has facilitated PPI in the following projects:

•  Improving anxiety assessment in Stroke and Acquired Brain injury: the validation of the Anxiety Intensity Scale Circles (AISCs), the Yale-anxiety, and Natural Language Processing (NLP) models
• Coronary bifurcation percutaneous coronary intervention: investigating a stentless strategy with drug coated balloons
• EASE - Evaluating Antidepressants for emotionaliSm after StrokE: A multi-centre, randomised, double-blind, placebo-controlled trial to establish the effect(s) of sertraline (50 mg once daily) in people with post -stroke emotionalism
• Exploring risks for women who have a pregnancy after bariatric surgery to inform pregnancy and postnatal care needs

She is also passionate about science communication, being involved with the Norwich Sciences Festival for the last 7 years aswell as delivering numerous talks. 

Alongside these research roles Jasmyn is a Associate Tutor teaching on Maths, Machine Learning, Artificial Intelligence and Programming Modules across undergraduate and postgraduate courses in CMP.  

I am currently pursing a PhD under the supervision of Dr Taoyang Wu (CMP) and Prof Cock Van Oosterhout (ENV) with a focus on developing Deep Learning Models to assess exitinction risk and recovery potential of species. 

I hold a Master of Science Degree (MSci) from UEA, where I completed 3 years following the BSc programme and one additional year to complete a masters research project.  During the first 3 years my study and research interestes here interdiciplinerary this high acheievements in modules which had a focus on:

• data science
• evolution
• molecular biology and genetics
• physiology
• health and disease

During my masters year my research concentrated on using a population of long-term monitored great tits (Parus major) and blue tits (Cyanistes caeruleus)  as a model for investigating corresspondance between social network manipulation and measuring cognition and behaviour in the wild. This involved extensive data analysis in R and python. Alongside my primary research, I collaborated closely with a PhD student investigating the gut microbiome in wild bird populations. My involvement included assisting with the capture and handling of birds in the field, collecting faecal samples for microbiome analysis, and processing samples in the laboratory using sterile techniques. Through this experience, I developed a range of wet lab skills, bulding on my already extablished experience in DNA extraction, PCR amplification, and gel electrophoresis. This strengthened my technical competencies but also deepened my understanding of host-microbiome interactions which led to me completing a short project where I review of research into the Gut-Brain axis aswell as a critical review of The Loss of Ancestral Microbiota and its Implications for Modern Human Health. 

Member, Computational Biology Lab

Member, Lifespan Health