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Deep Learning-based Characterisation of Protein Aggregation in amyotrophic lateral sclerosis (ALS)

   School of Engineering & Physical Sciences

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  Dr M Vallejo  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Amyotrophic lateral sclerosis (ALS) is a rapidly debilitating neurodegenerative disease that affects motor neurons [1]. Patients develop progressive muscle weakness, leading to death due to respiratory failure, which typically occurs after 3–5 years of symptom onset. ALS affects 1.75 – 3 out of 100,000 individuals per year [2]. The existence of protein TDP-43 aggregates in affected motor neurons is still a poorly understood hallmark [4]. 

This project aims at increasing the understanding of these structures. To achieve this goal, we will use an image dataset where TDP-43 proteins were visualised using super-resolution microscopy by two different types of dyes, aptamers and antibodies. This dataset was generated in the school of chemistry at the University of Edinburgh using post-mortem tissue of ALS patients extracted from the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) cohort [3]. 

In order to understand the disease progression, it is necessary to characterise in more detail how protein assemblies presented in different cells, neurons and glia are correlated with different levels of severity of the disease (presented as annotations given by the clinicians). The idea is to explore which image representation can better characterise the aggregation and apply different machine learning techniques, such as convolutional neural networks, to extend the understanding of how the TDP-43 aggregates behave at an individual level.

All applicants must have or expect to have a 1st class MChem, MPhys, MEng, MSci or equivalent degree by Summer 2023. Selection will be based on academic excellence and research potential, and all short-listed applicants will be interviewed (in person or via Teams).

Closing Date: 9 of February 2023. All successful candidates must commence studies as soon as possible

How to Apply


When applying through the Heriot-Watt on-line system please ensure you provide the following information:

(a) in ‘Study Option’

You will need to select ‘Edinburgh’ and ‘Postgraduate Research’. ‘Programme’ presents you with a drop-down menu. Choose Bio-engineering and Bio-sciences PhD/Chemistry PhD/Physics PhD/Electrical PhD/ Mechanical Engineering PhD for study option

(b) in ‘Research Project Information’

You will be provided with a free text box for details of your research project. Enter Title of the project for which you are applying and also enter the supervisor’s name.

This information will greatly assist us in tracking your application.

For questions about the application process, please contact [Email Address Removed]


[1] Ravits, J. M., and La Spada, A. R. (2009). ALS motor phenotype heterogeneity, focality, and spread: deconstructing motor neuron degeneration. Neurology 73, 805–811. doi: 10.1212/wnl.0b013e3181b6bbbd
[2] Naruse, H., Ishiura, H., Mitsui, J., Takahashi, Y., Matsukawa, T., Tanaka, M., et al. (2019). Burden of rare variants in causative genes for amyotrophic lateral sclerosis (ALS) accelerates age at onset of ALS. J. Neurol. Neurosurg. Psychiatry 90, 537–542. doi: 10.1136/jnnp-2018-318568
[3] De Icaza Valenzuela, M.M., Bak, T.H., Thompson, H.E., Colville, S., Pal, S. and Abrahams, S., 2021. Validation of The Edinburgh Cognitive and Behavioural ALS Screen (ECAS) in behavioural variant Frontotemporal Dementia and Alzheimer's Disease. International Journal of Geriatric Psychiatry.
[4] Tan RH, Ke YD, Ittner LM, Halliday GM. ALS/FTLD: experimental models and reality. Acta Neuropathol 2017; 133: 177-196
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