Machine Learning Applied to Fluorescence Microscopy Images to Assist the Development of Malaria Transmission-Blocking Drugs

Malaria is a serious disease and one of the major health challenges in the world today. African countries are particularly badly affected, carrying the overwhelming majority of malaria cases. Children under 5 are the most vulnerable.<br /> <br /> Therefore, the development of new types of drugs, such as transmission-blocking drugs (TBDs), is crucial to handling the problem. Unlike traditional drugs, TBDs prevent transmission by targeting Plasmodium (the parasite responsible for malaria transmission).<br /> <br /> Analysis of fluorescence microscopy images is one way to assist in the development of TBDs. Fluorescence microscopy is often used to trace small features, such as microbes or chemical compounds, in human cells. It is used to estimate how drugs affect the transmission of Plasmodium.<br /> <br /> In the past decade, machine learning (and deep learning methods in particular) have become increasingly popular in image analysis. This also includes the analysis of the Fluorescence Microscopy Images.<br /> <br /> The project will focus on developing and evaluating novel ML-based methods to analyse fluorescence microscopy images of cells affected by Malaria and/or TBDs to test their efficiency. The methods will be tested using real-life biological data provided by one of the co-supervisors.<br /> <br /> The project will be done in collaboration with experts from LSHTM and ETH Zurich.<br />

<p style="margin-bottom:11px">References</p> <p>[1] Tsebriy O, Khomiak A, Miguel-Blanco C, Sparkes PC, Gioli M, et al. (2023) Machine learning-based phenotypic imaging to characterise the targetable biology of Plasmodium falciparum male gametocytes for the development of transmission-blocking antimalarials. PLOS Pathogens 19(10): e1011711. <a href="https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1011711">https://doi.org/10.1371/journal.ppat.1011711</a></p> <p>[2] Juan C Caicedo, Jonathan Roth, Allen Goodman, Tim Becker, Kyle W Karhohs, Matthieu Broisin, Csaba Molnar, Claire McQuin, Shantanu Singh, Fabian J Theis, and Anne E Carpenter. Evaluation of deep learning strategies for nucleus segmentation in fluorescence images. Cytometry A, 95(9): 952-965, July 2019. <a href="https://doi.org/10.1002/cyto.a.23863">https://doi.org/10.1002/cyto.a.23863</a></p>

<p>To apply for this project you will need to make a formal application for research degree study through the <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University website</a>. You will need to create a login ID with a username and PIN. </p> <p>•    For <strong>Application type</strong> please select <strong>Research Degrees – Research Postgraduate</strong>. <br /> •    The admission year for this project is <strong>2027/28</strong> Academic Year. <br /> •    You will need to select your <strong>Planned Course of Study</strong> from a drop-down menu. For this project, scroll down and select <strong>PHP Statistics Full Time.</strong> <br /> •    The project start date for this project is <strong>1 October 2027</strong>, please use this as your <strong>Proposed Start Date of Research</strong>. <br /> •    Please state clearly in the<strong> Research Information Section</strong> that the research degree you wish to be considered for is <strong>Machine Learning Applied to Fluorescence Microscopy Images to Assist the Development of Malaria Transmission-Blocking Drugs</strong> as well as <a href="https://eps.leeds.ac.uk/faculty-engineering-physical-sciences/staff/10654/dr-sofya-titarenko">Dr Sofya Titarenko</a> as your proposed supervisor.</p> <p><strong>Please state clearly in the Finance section</strong>, <strong>the funding that you are applying for, if you are self-funding or externally sponsored</strong>.</p> <p>More information on how to apply is available on our website <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">here</a>. You will be required to provide a personal statement which outlines your interest in the project you are applying for, why you have chosen it and how your skills map onto the requirements of the project.</p> <p>We will assess applications continuously as we receive them. We welcome and strongly encourage any potential applicants to contact the supervisor(s) for an informal discussion, prior to applying, and recommend submitting your application early.</p> <p><strong>If you are applying with external sponsorship or you are funding your own study, please ensure you provide your supporting documents at the point you submit your application:</strong></p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date including the grading scheme</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul> <p>If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below).</p> <p><em>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.</em></p>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<p>This is a non funded PhD project. Applicants are expected to be self funded or to secure external funding.</p> <p>You can find out more about our Funding Opportunities on our <a href="https://phd.leeds.ac.uk/">Postgraduate Research Opportunities</a> website.</p> <p><strong>Important: </strong>Please note that all costs associated with your arrival at Leeds (<a href="https://www.leeds.ac.uk/international-visas-immigration/doc/applying-student-visa">visa, Immigration Health Surcharge</a>, flights etc) would have to be met by yourself, or you will need to find an alternative funding source.</p>

<p>For general enquiries about your application, please contact PGR admissions by email to <a href="mailto:epspgradmissions@leeds.ac.uk">epspgradmissions@leeds.ac.uk</a></p> <p>For questions about the research project, please contact Dr Sofya Titarenko by email to <a href="mailto:S.Titarenko@leeds.ac.uk">S.Titarenko@leeds.ac.uk</a></p>