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<p class="MsoNormal"><span lang="EN-US">Our neuroscience research team at University College London is looking for a postdoctoral researcher to study how large populations of neurons work together to process information. This work involves analyzing simultaneous
recordings of neurons from across the brain, using advanced tools from statistics and machine learning.<o:p></o:p></span></p>
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<span lang="EN-US">This position would suit candidates with a first degree in Mathematics, Statistics, Computer Science, Engineering, Physics, Neuroscience, or a related field. Strong programming skills are essential (we mostly use Python and MATLAB). Knowledge
of neuroscience is desirable, but we will also consider candidates with a machine learning background who are interested in learning neurobiology. The job involves analyzing experimental data, but does not require performing experiments, and we encourage
applicants with a background in theoretical neuroscience or data science to apply.
<o:p></o:p></span></p>
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<span lang="EN-US">To apply, go to </span><a href="https://www.ucl.ac.uk/human-resources/working-ucl/jobs-ucl"><span lang="EN-US">https://www.ucl.ac.uk/human-resources/working-ucl/jobs-ucl</span></a><span lang="EN-US" style="color:#333333">,
</span><span lang="EN-US">click “Search for a job” and enter reference number 1805922.<o:p></o:p></span></p>
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<span lang="EN-US">Women and unrepresented minorities are particularly encouraged to apply. The deadline for applications in 12 July 2019.<o:p></o:p></span></p>
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<p class="MsoNormal">---------------------<o:p></o:p></p>
<p class="MsoNormal">Kenneth D. Harris<o:p></o:p></p>
<p class="MsoNormal">Professor of Quantitative Neuroscience<o:p></o:p></p>
<p class="MsoNormal">Institute of Neurology, Department of Neuroscience, Physiology, and Pharmacology<o:p></o:p></p>
<p class="MsoNormal">University College London<o:p></o:p></p>
<p class="MsoNormal">Cruciform Building, Gower Street<o:p></o:p></p>
<p class="MsoNormal">London WC1E 9BT<o:p></o:p></p>
<p class="MsoNormal"><span lang="EN-US">Phone: +44 (0) 20 7679 0709<o:p></o:p></span></p>
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