Postdoctoral Training Fellow

Updated: about 1 month ago
Location: London, ENGLAND
Job Type: FullTime
Deadline: 04 Oct 2020

<p><strong>Job title</strong>: Postdoctoral Training Fellow – Computational biologist </p>
<p><strong>Location:</strong> The Francis Crick Institute, Midland Road, London</p>
<p><strong>Contract: </strong>Fixed term (4 years), Full time</p>
<p><strong>Salary: </strong> Competitive with benefits, subject to skills and experience</p>
<p><strong>Vacancy ID</strong>: 14728</p>
<p>The Cancer Epigenetics Lab <a href=" ">"> is looking for an enthusiastic postdoctoral fellow with strong computational expertise, interested in studying how disruption of epigenetic control, alterations in chromatin structure and transcriptional deregulation contribute to cancer development. The successful candidate will be expected to develop a project addressing important biological questions related to: <strong>robustness and plasticity of epigenetic regulation</strong>, <strong>transcriptional stochasticity</strong>, <strong>phenotypic intratumour heterogeneity</strong>, or any other interesting topic that fits into the general interests of the lab. The appointed postdoctoral fellow will both work side-by-side with experimentalists and mine publically available datasets, and will join an active community of computational scientists in the institute. </p>
<p>We are based at the Francis Crick Institute in central London <a href=" ">"></a>. We benefit from core-funding by Cancer Research UK, the UK Medical Research Council, and the Wellcome Trust, have access to state-of-the-art facilities and Science Technology Platform <a href=" ">">https://www.c..., and enjoy a collaborative and multidisciplinary research culture. Some recent studies by the group:</p>
<p>Torres et al, <strong><em>Science</em></strong> 2016 – epigenetic basis of intratumour heterogeneity</p>
<p>Chakrabarti et al, <strong><em>Molecular Cell</em></strong> 2019 – CRISPR mechanisms</p>
<p>Mourikis et al, <strong><em>Nature Communications</em></strong> 2019 – machine learning to identify cancer drivers</p>
<p><strong>The project</strong></p>
<p>The successful candidate will have the freedom and responsibility to develop and lead an ambitious project addressing important biological questions that will help us understand:</p>
<li>The basis of epigenetic robustness in normal cells and how this is compromised in cancer</li>
<li>The transcriptional consequences of destabilizing the network of epigenetic regulators in cancer</li>
<li>Whether we can predict epigenetic vulnerabilities based on how the regulatory network is disrupted in a patient</li>
<li>The role of transcriptional stochasticity and phenotypic heterogeneity in cancer</li>
<p><strong>Qualifications </strong></p>
<li>Strong quantitative research background with a PhD in areas such as computer science/bioinformatics, biology (molecular biology, genomics, with strong computational expertise), or mathematics/physics (with excellent understanding of biology and genomics)</li>
<li>Demonstrated ability to perform high-quality research, and capacity to formulate hypotheses, test them and follow through</li>
<li>Experience with single-cell RNA-seq and/or transcriptional regulatory networks and/or systems biology is highly desirable</li>
<li>Strong and evident motivation, creativity, excellent communication skills and genuine enthusiasm for science</li>
<p>If you are interested in applying for this role, please apply via our website.</p>
<p>The closing date for applications is 04 October 2020 at 23:45.</p>
<p>All offers of employment are subject to successful security screening and continuous eligibility to work in the United Kingdom.</p>

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