<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>About on James Read-Tannock</title><link>https://jreadtannock.com/</link><description>Recent content in About on James Read-Tannock</description><generator>Hugo</generator><language>en-gb</language><lastBuildDate>Mon, 01 Jan 0001 00:00:00 +0000</lastBuildDate><atom:link href="https://jreadtannock.com/index.xml" rel="self" type="application/rss+xml"/><item><title>Coming soon!</title><link>https://jreadtannock.com/research/current-project/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jreadtannock.com/research/current-project/</guid><description/></item><item><title>CV</title><link>https://jreadtannock.com/cv/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jreadtannock.com/cv/</guid><description>Education 2022–2026 · PhD, Computational Neuroimaging, University of Nottingham. BBSRC-funded research on structural brain networks, neuroimaging methods, and neurodegeneration. 2021–2022 · MSc Computational Neuroscience, Cognition &amp;amp; AI, University of Nottingham — Distinction. 2014–2017 · BSc Economics, SOAS, University of London — Upper Second-Class Honours. Experience 2026–present · Newcastle University. January–April 2026 · Research &amp;amp; Development Intern, icometrix. Longitudinal brain atrophy measurement and inter-scanner harmonisation. 2023–2024 · Graduate Teaching Assistant, University of Nottingham.</description></item><item><title>Publications</title><link>https://jreadtannock.com/publications/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jreadtannock.com/publications/</guid><description> Read-Tannock, J., Reid, A., Farcot, E., Schürmann, M., &amp;amp; Madan, C. R. (2026). Bias in structural MRI correlates of delay discounting due to head motion. Human Brain Mapping, 47(3), e70474. doi:10.1002/hbm.70474 Read-Tannock, J., Reid, A., Farcot, E., Schürmann, M., &amp;amp; Madan, C. R. (2026). Graph-theoretic analyses of structural covariance networks: quantifying the false discovery rate. bioRxiv [preprint]. doi:10.64898/2026.06.23.733999</description></item></channel></rss>