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A multilevel computational framework for brain diseases


Key facts

Type of research degree
Application deadline
Ongoing deadline
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>

A large part of computational brain science is concerned with generating models of the brain that can help us understand its function. These models range in complexity and biological accuracy, with system-level models often being the least biologically detailed ones. Increasing computational power has opened the possibility to turn models of the brain, or of its components, into simulations with an unprecedented level of detail. However, there is still a gap between biologically inspired models, used to address molecular and cellular questions, and models based on dynamical systems which can account for complex neurological (e.g. EEG, fMRI) and behavioural observations. For example, traditionally, the epileptic brain has been interpreted using dynamical system models (e.g. neural mass) with loose biological bases, while the molecular mechanisms causing epileptic phenotypes were investigated experimentally and using biophysical simulations. Recent academic work has shown that models of cellular features can be matched to standard clinical measures such as EEG showing seizure-like behavior. Here, we propose to expand the molecules-to-organism simulation approach by generating a framework that allows the implementation of different biological mechanisms to test whether their therapeutic modulation would be efficacious in reducing the likelihood of seizures.<br /> <br /> For brain diseases, such as epilepsy, extracting high-level dynamic features from biophysically accurate neuronal and network simulations can provide predictive information on seizures and on whether these can be mitigated by a given treatment. To test this hypothesis, we will use sophisticated computational methods, including machine learning techniques, to build a simulation framework spanning across different levels, from molecules to patients. The framework will be informed by experimental and clinical data and it will lay its foundation in well tested open-source simulation environments such as NEURON., NEST and The Virtual Brain, part of the EBRAIN infrastructure funded through the Human Brain Project.<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.

<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 Planned Course of Study section that you are applying for <em><strong>PHD Computing FT</strong></em> and in the research information section&nbsp;that the research project you wish to be considered for is &lsquo;<em><strong>A multilevel computational framework for brain diseases</strong></em>&rsquo; 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>&nbsp;</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>