Applications were invited from PhD and MScR postgrad students from across Edinburgh who are using imaging in research.

ESRIC is always very supportive of the PhD Expo, run by Edinburgh Imaging, and this year our ESRIC facility manager, Ali Dun, was on the judging panel. This event is a rare chance for PhD students to really challenge themselves and hone their presenting skills in an audience of fellow PhD students, post-doctorates and group leaders in the field of microscopy (not just clinical and medical imaging). PhD students from all areas of microscopy were invited to apply to present their work or just come along to this free networking event, with chances to present posters and meet with fellow imagers and industry partners. The attendance by Industry representatives is a great opportunity to explore a different side of science, see how the work we do is put into practice and discover possible alternative career trajectories. There were significant prizes for the best presentation! 

The winners were;

  •  Best Clinical Oral presentation, receiving £200:

    Student: Jack ANDREWS

    Title: “18F-FLUORIDE PET-MR IN VALVULAR AND CORONARY HEART DISEASE”

    Highly Commended Clinical Oral presentation

    Student: Beth YORK

    Title: "Quantitative imaging biomarkers of demyelination and remyelination: reproducibility of MTsat vs. MTR."  

  •  Best Preclinical Oral presentation, receiving £200:

    Student: Benjamin THOMAS

    Title: "PET/CT: identifying sex differences in glucose disposal in calorie restriction"

    Highly Commended Preclinical Oral presentation

    Student: Adrian GARCIA BURGOS

    Title: “Three-dimensional Super-Resolution imaging in living intact pancreatic islets” 

  •  Best Visual presentation receiving £50:

    Student: Sally VANDEN-HEHIR

    Title: "New tools for visualising nanoparticle delivery to promote healthy remyelination"

    Highly Commended Visual presentation:

    Student: Wendy MCDOUGALD

    Title: "Multi-centre standardization of preclinical PET/CT imaging: a necessary step towards achieving translational imaging datasets"