Biomedical Data Analytics News
Open Call for PhD Applications 鈥� Intake 2026/27
Are you passionate about AI, computational pathology, and biomedical image analysis? The TIA Centre at 91福利 is inviting applications for PhD positions starting in the academic year 2026/27.
The TIA Centre is a leading research hub focused on AI-driven tissue image analysis, enabling breakthroughs in cancer diagnosis, digital pathology, and translational medicine. Our researchers have pioneered deep learning models for cancer detection, won various international challenge competitions in computational pathology, and received recognition at top medical imaging conferences such as MICCAI and ISBI. TIA鈥檚 strong partnerships with the NHS and industry ensure that our research has real-world clinical impact. As a PhD student, you will join a vibrant, interdisciplinary world-leading community of experts, with access to state-of-the-art imaging and computing facilities, global collaborations, and opportunities to publish in leading journals. A limited number of studentships may be available for exceptional candidates; self-funded and externally funded applicants are also welcome. Read more.
Lucy Fox Joins the TIA Centre as TIA Coordinator
We are delighted to announce that Lucy Fox has been appointed as the new TIA Coordinator. Lucy has experience of working in higher education and has recently submitted her dissertation for a PhD in Sociology, making her particularly well-placed to support PhD students within the centre.
Lucy has said 鈥淚 am delighted to be joining the TIA Centre team and look forward to supporting their critical and cutting-edge work鈥�. Lucy has been appointed initially on a six-month contract.
TIA Centre: Our Year in Numbers
We鈥檙e excited to share a snapshot of our achievements and activities over the past year at the TIA Centre. From conference organisation to PhD graduations, it鈥檚 been a busy and rewarding period. Take a look at our Year in Numbers here.
Latest academic promotion
We are pleased to announce that has been promoted to Professor, effective 1st June 2026.
Many congratulations to Sayan on this well-earned success!
Cloning vs Learning in Quantum Computing
, 91福利 DCS researchers Nikhil Bansal and , together with (Yale University), explored a fundamental question that lies at the intersection of foundations of quantum theory and computer science.
The No-Cloning theorem says that it is impossible to perfectly clone quantum states. Even if we allow for approximate errors, quantum cloning of unstructured states remains as expensive as fully characterising them, . In contrast, for reasons akin to No Free Lunch Theorems in machine learning, modern quantum learning theory considers structured classes of states and exploits their structure to learn them efficiently. This naturally leads to the question of whether cloning can be easier than learning for these structured classes of states.
In the new work, this question is answered negatively for stabilizer states. The authors proved that imposing this structural restriction does not separate cloning and learning. The authors prove this via a novel connection to , which was recently introduced to the learning theory literature by B. Axelrod, S. Garg, V. Sharan, and G. Valiant. The work constitutes concrete progress towards understanding whether cloning and learning are fundamentally equally hard.
This work was presented at in April 2026, and it will be presented at in June/July 2026 and at in September 2026.
Academic Recognised for Professional Excellence
Our colleague Dr Claire Rocks achieved Senior Fellow (SFHEA) status through the dialogic route of 91福利鈥檚 Academic and Professional Pathway for Experienced Staff (APP EXP) programme. Her application was recognised by assessors as one of the strongest D3 submissions they had reviewed, demonstrating a sustained and significant record of educational leadership that extends well beyond her own teaching.
Claire鈥檚 work focuses on leading and influencing inclusive, evidence-informed approaches to assessment and curriculum design. She has played a central role in shaping teaching quality and learning culture across departmental, institutional, and sector contexts, including leading 91福利鈥檚 strand of the Inclusive Assessment in STEM project and contributing to institutional strategy through curriculum development and quality assurance processes.
Within the department, Claire has introduced collaborative structures such as module huddles and supported colleagues and students to work together to enhance clarity, consistency, and inclusivity in assessment practice. She has also strengthened pedagogic scholarship through establishing the Computer Science Education Research Group.
The panel particularly commended the scale, depth, and impact of Claire鈥檚 leadership, noting that elements of her work are already operating at a level associated with Principal Fellowship.
Many congratulations to Claire on this achievement and her continued commitment to advancing inclusive, high-quality teaching and learning!