causal inference and machine learning
Applications are invited for a 4 year PhD studentship, within the laboratory of Dr Miguel Martins at the MRC Toxicology Unit, commencing October 2023.
Neurodegenerative diseases affect millions of people. Alzheimer's and Parkinson's diseases (respectively, AD and PD) are the most common forms of neurodegenerative diseases and the likelihood of developing either one of these diseases rises dramatically with age. Both AD and PD are caused by neuronal cell death and the risk of developing either one of these diseases is linked to a combination of a person's genes and their environment. Differences in the individual's DNA sequence could lead to increased or decreased expression of genes involved in these pathways, indicating different genes might drive neurodegeneration in different AD patients.
A better understanding of the genes that cause or protect against neurodegenerative diseases will elucidate the potential drugs that can cause or delay neurodegeneration. In this project, we will use a computational approach to systematically investigate genes that might increase the risk of developing AD as well as AD-pathology. Specifically, we will use causal inference to model how individual genetic variations increase the expression of a gene, and whether it is also associated with AD risk. We will then use network analysis to investigate the pathways that the identified genes belong to. Next, we will use unsupervised machine learning methods to identify molecular inhibitors of the target genes. Finally, we will validate whether these inhibitors increase or decrease neurodegeneration in an animal model of AD. Taken together, this project combines different computational approaches (causal inference, pathway analysis and machine learning) with wet lab experiments.
The successful candidate will gain experience in multiple areas of computational and experimental biology, such as molecular and cell biology, genetics, high-throughput techniques, genomics, and advanced bioinformatics analyses. Applicants must be imaginative, highly motivated, and enthusiastic, with the capacity to accept and learn from failure. A familiarity and passion with numerical approaches (such as mathematics, bioinformatics, or computer programming) would be highly advantageous.
The Medical Research Council (MRC) Toxicology Unit is a leading International Research Institute within the School of Biological Sciences, University of Cambridge. The Unit delivers mechanistic toxicology research, pursuing hypothesis-driven toxicological questions with a particular focus on the study of the causal links between exposure to endogenous and exogenous toxicants, molecular initiating events and adverse outcome pathways. The Unit's overall aims are to carry out pioneering research which leads to improved health and to train and mentor the next generation of toxicologists.
Full funding covering Maintenance and the University Composition Fee (Home Fee rate) is provided Maintenance is currently £19,250.
This studentship is open to UK citizens or overseas students who meet the UK residency requirements (home fees) or are able to augment the funds to cover the extra costs associated with international student fees.
Applicants should have or shortly expect to obtain a first or good upper second-class degree from a UK university, or an equivalent standard from an overseas university, in a relevant subject area. Strong analytical skills, in addition to creativity, curiosity, enthusiasm, and the ability to work in a team are essential.
You are strongly recommended to contact the project supervisor prior to submitting your formal application to find out more about the project and eligibility: Dr Miguel Martins: [email protected]
Information regarding the application process can be found at: https: // www. mrc-tox.cam.ac.uk/phd-programme
If you have any queries regarding the application process, please contact [email protected]
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.Department/Location
MRC Toxicology Unit, CambridgeReference
14 February 2023Closing date
31 March 2023