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A computational framework of associative learning and memory formation


Key facts

Type of research degree
Application deadline
Ongoing deadline
Project start date
Sunday 1 October 2023
Country eligibility
International (open to all nationalities, including the UK)
Competition funded
Source of funding
University of Leeds
Dr Jian Liu
School of Computing
<h2 class="heading hide-accessible">Summary</h2>

When a musician plays piano, she needs to recall a sequence of notes. Neuroscientists seek to understand how brain activity gives rise to a timed sequence of events, as a result of associative learning and memory formation. These behaviours are formed within neuronal networks, which consist of the building blocks of single cells and connections between cells (synapses). Most neuroscience research is focused on neural signalling that happens in individual brain nerve cells (cortical neurons). However, there are other types of activities within and above individual neurons. Within neurons, each individual neuron has a tree-like structure ending in thousands of tiny connection points (synapses forming on spines). Above any one neuron, there are populations of neurons that work in concert within a microcircuit. Both synaptic spines and neuronal populations are activated and represented as neural signals. Recent advances in experimental techniques enable observation of neural signalling at both spatial scales. At fine scale, one can measure activities of a subset of synapse/spines in one neuron. In contrast, at the coarse scale, one can simultaneously observe a subset of neurons in mutual activation. When we learn a sequence of music notes, it is likely that neuronal signals at spines and populations display similar dynamics, and that they are activated in a sequence after learning. However, the functions and mechanisms of sequential learning and memory are not well understood, as it is quite difficult to observe both types of activity simultaneously. Thus, a computational approach is necessary, as it will give us new insights into the learning process that happens on both spatial scales. <br /> <br /> The aim of this project is to describe learning process leveraging neuroscience data in animals and humans and developing a novel modelling framework using biological principles of neurons and synapses. The outcome of this project will provide new insights into the memory mechanisms of humans, contribute to novel neural network models for learning and memory, and develop novel methodologies for next-generation artificial intelligence. <br /> <br /> The supervision team has expertise in machine learning, computational neuroscience, animal and human neuroscience, brain disease, clinical neuroscience, with regularly published research papers at the very top venues in related fields.<br />

<h2 class="heading">How to apply</h2>

<p>Formal applications for research degree study should be made online through the&nbsp;<a href="">University&#39;s website</a>. Please state clearly&nbsp;in the Programme of Study that you are applying for <em><strong>PHD&nbsp;Computing FT</strong></em>&nbsp;and in the research information section&nbsp;that the research project you wish to be considered for is <em><strong>A&nbsp;computational framework of associative learning and memory formation</strong></em>&nbsp;as well as&nbsp;<a href="">Dr Jian Liu</a> as your proposed supervisor.</p> <p>If English is not your first language, you must provide evidence that you meet the University&#39;s minimum English language requirements (below).</p> <p style="margin-bottom:11px"><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> <p class="MsoNoSpacing">Applications will be considered on an ongoing basis. &nbsp;Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. &nbsp;We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed.</p> <p>Please note that you must provide the following documents at the point you submit your application:</p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> <li>Funding information including any alternative sources of funding that you are applying for or if you are able to pay your own fees and maintenance</li> </ul>

<h2 class="heading heading--sm">Entry requirements</h2>

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.

<h2 class="heading heading--sm">English language requirements</h2>

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.5 overall with at least 6.5 in writing and at least 6.0 in reading, 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.

<h2 class="heading">Funding on offer</h2>

<p style="margin-bottom:12px"><strong>Self-Funded or externally sponsored students are welcome to apply.</strong></p> <p><strong>UK</strong>&nbsp;&ndash;&nbsp;The&nbsp;<a href="">Leeds Doctoral Scholarships</a>, <a href="">Leeds Opportunity Research Scholarship</a> and <a href="">School of Computing Scholarships</a> are available to UK applicants. <a href="">Alumni Bursary</a> is available to graduates of the University of Leeds.</p> <p><strong>Non-UK</strong> &ndash; The <a href="">School of Computing Scholarships</a> are available to all International applicants. The&nbsp;<a href="">China Scholarship Council - University of Leeds Scholarship</a>&nbsp;is available to nationals of China. The&nbsp;<a href="">Leeds Marshall Scholarship</a>&nbsp;is available to support US citizens. <a href="">Alumni Bursary</a> is available to graduates of the University of Leeds.</p> <p><strong>Important:</strong>&nbsp; Any costs associated with your arrival at the University of Leeds to start your PhD including flights, immigration health surcharge/medical insurance and Visa costs are not covered under this studentship.</p> <p>Please refer to the <a href="">UKCISA</a> website for information regarding Fee Status for Non-UK Nationals.</p>

<h2 class="heading">Contact details</h2>

<p>For further information regarding the project, please contact: Dr Jian Liu e: <a href=""></a></p> <p>For further information regarding your application, please contact Doctoral College Admissions:&nbsp; e:&nbsp;<a href=""></a></p>

<h3 class="heading heading--sm">Linked research areas</h3>