2019

Understanding the effect of antibiotic combinations: a quantitative approach

Supervisors: Meriem El Karoui, Rosalind Allen

Project Description:

Our society is currently facing an important problem with the rise of multiple antibiotic resistant bacterial strains. As the development of new antibiotics has stalled in recent years, new strategies are urgently needed to supplement current available therapies. This involves increasing the efficiency of already available antibiotics as well as identifying new targets.

Other: 

Deep learning based analysis of DNA replication in primary mammalian cells

Supervisors: Sara Buonomo, Hakan Bilen

Project Description:

This ground-breaking research project aims to develop deep learning (and machine learning) techniques to the study of the temporal and spatial control of DNA replication in mouse embryonic stem cells. The goal is to design deep learning algorithms that can learn from large amounts of images to classify them ACCURATELY and EXPLAINABLY.

Other: 

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