Current summer students
Summer Student 2021: Ali Mehmood
Ali’s project seeks to use a hybrid of computer learning and animal free laboratory techniques to develop a prognostic marker for head and neck cancer.
Summer Student 2021: Amir Fard
Amir will use 3D human organoid models of normal colon tissue and of colon cancer to help to identify new treatment strategies.
Summer Student 2021: Dania Alkhatib
Dania will use artificial intelligence (AI) approaches to allow her to address an important unmet clinical need: can we predict tumour recurrence for head and neck cancer.
Summer Student 2021: Emily-Rose Martin
Emily-Rose will work to establish a new method of growing neuron-like cells to study Autism spectrum disorder (ASD) which is one of the most common neurodevelopmental disorders.
Summer Student 2021: Fiona Nhi Dang
Fiona will investigate the physical and biological changes that occur within the body as a result of heart attack and severe haemorrhage.
Summer Student 2021: Imogen Carmichael
Imogen will test if an animal-free media can be used to grow and differentiate a cellular model of dementia.
Summer Student 2021: Izzy Breithaupt
Izzy’s project will create, characterise and adopt an animal free approach towards genotoxicity testing of a variety of different human toxicants, using advanced human lung and liver model systems.
Summer Student 2021: Morwenna Oldfield
Morwenna will build a cell-based membrane which will act as a model for the cornea allowing her to find novel ways of delivering drugs without relying on testing in animals.
Summer Student 2021: Riddhi Sharma
Riddhi will develop a method to study the genetic and environmental causes of Parkinson’s disease in human brain cell lines, to assess whether the cells are entering a diseased state.
Summer Student 2021: Rosie Davis
Rosie’s project will develop better human relevant models of bowel cancer to allow scientists to study how drugs penetrate dense cancer tissue without using animals.
Summer Student 2021: Yutong Chen
Yutong will explore state-of-the-art artificial intelligence-based methods to reduce the time taken to acquire magnetic resonance images (MRI).
Page last modified on July 5, 2021 9:52 am
