Link Day brings together Doctoral Researchers and Staff from the four EPSRC-funded Mobility Pilot Doctoral Training Partnerships (DTPs) and their invited guests.
Sharing the aim of widening participation in doctoral training to include specifically those from industry and other non-academic backgrounds, the four Mobility Pilot DTPs are the:
Link Day 2023 will take place on Monday, 4th September 2023 in the Graduate Centre on the Mile End Campus. The Graduate Centre is building n. 18 on the Mile End campus map [PDF 936KB].
Please note that only Doctoral Researchers and staff from the four Mobility Pilot DTPs and invited guests can attend Link Day 2023. RSVPs closed in August.
For more information, please see the sections below:
Event Schedule
Directions and Accommodation
Participants
Registration
Refreshments
Ground Floor Foyer, Graduate Centre
6th Floor Foyer, Graduate Centre
The nearest stations on the London Underground are:
You can plan your journey using the Transport for London website
More information about the Mile End Campus
The Graduate Centre is building n. 18 on the Mile End campus map [PDF 936KB].
The nearest campus entrance is on Bancroft Road.
Find the QMUL Graduate Centre on Google Maps.
If required, the nearest hotel to the Mile End Campus is the Travelodge London Mile End.
Alternatively, the Travelodge London Bethnal Green is about 1 mile away from the Graduate Centre.
Almost 40 people attended Link Day 2023 - and in doing so, helped make Link Day a success.
Read about some of our Link Day participants below (in alphabetical order by first name)
Queen Mary University of London (DTP Researcher)
Research interests: Population Genetics (with a focus on mosquitoes / Malaria)
Contact Amelia: Email; LinkedIn
University of Southampton (DTP Researcher)
Research interests: Microphone arrays for enhanced identification and classification of target signals in noisy environments
Email Christopher
Brunel University London (DTP Staff)
Research Interests: Manufacturing
Email Diane
Queen Mary University of London (DTP Staff)
Research Interests: my work is related to applying statistical methods to 'unfold' or invert high dimensional observed data to correct for detector distortions. These inversion problems are suitable for machine learning approaches.
Contact Eram: Email; LinkedIn; Staff Profile
Manager of the DCE CDT. My research interests include: the discursive devaluation and gendering of admin work; higher education studies, equality & diversity.
Contact Gabriella: Email; LinkedIn
Research Interests: Where is [some of] the Physical Internet and Who owns it?
Contact George: Email; Twitter; Website
Research Interests: Grid-edge technologies, energy efficiency, optimization techniques for power systems with renewable energy, machine learning for energy systems, power quality and smart metering.
Email Ioana
University of York (DTP Staff)
Jen is the Admin Manager for York's participation in the EPSRC Mobility DTP.
Contact Jen: Email; LinkedIn
Research Interests: VR, haptics, generative AI, education, education, dental, education technology, NLP
Contact Job: Email; LinkedIn
Research Interests: Structuring Clinical Data in Electronic Health Records using Language Models
Email Joseph
Queen Mary University of London (Academic Supervisor)
Our research group integrates population genomics with data science to address fundamental questions in evolutionary biology including in human evolution and disease susceptibility.
Email Matteo
Maritime operations of the future will seek to become more connected and distributed, especially with the introduction of autonomous agents and the benefits which they bring. My chosen area of interest explore the definition of this new type of capability, ways in which autonomy can be applied, how it can be implemented and how it can be managed
Contact Nikhil: Email; LinkedIn
Research Interests: The cannabinoid receptors CB1 and CB2 belong to the wide family of GPCR proteins which are responsible for the mediation of many cellular responses. Although both CB1 and CB2 receptors may co-exist, CB1 receptors are found principally in the brain and central nervous system and are involved in the regulation of neurotransmitter release. The abundance of both receptor types in the body exhibiting a wide range of functions makes them obvious targets in drug design campaigns where effective ligand design can affect the receptor signaling processes, mimicking the natural endocannabinoid system. This work uses a variety Neural Network methodologies to generate de novo libraries of compounds that can be developed into lead compounds for biological screening with the specific aim of targeting the endocannabinoid system.
Contact Peter: Email; LinkedIn
There are thousands of mutations in a tumor cell, but only a fraction of these are dangerous and need to be treated. Identifying these mutations remains a big challenge in cancer treatment. The advancement of AI in this field is promising, and my research will hopefully bring us closer to solving this problem. I will focus on using AI to predict protein mutations. More specifically, I am looking at using graph neural networks to resemble protein molecules and will develop an AI tool to predict which “knockout” of genes, i.e. genes that are removed from the DNA, denatures the protein. The AI tool developed will be validated with a novel CRISPR technique in the lab.
Contact Pryanka: Email; LinkedIn; Twitter
University of York (DTP Researcher)
Research Interests: Valorisation of agricultural residues
Contact Rashmi: Email; LinkedIn
Research Interests: How naturally occurring space weather may impact the data being transported via FSOC and what novel mitigations could be put in place to enhance data transfer rates.
Contact Robert: Email; LinkedIn
University of Southampton (DTP Staff)
Research Interests: Tribology, sensing, coatings, antifouling, low drag and surface engineering
Contact Robert: Email; LinkedIn; Staff Profile
Research Interests: Neural Rendering and Computational Photography
Email Sibi
Research Interests: Embedding Green Chemistry into Consumer Goods Ecodesign
Contact Victor: Email; LinkedIn