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<p dir="auto">What will machine learning mean for creativity? We're recruiting a machine learning post-doc for a cool interdisciplinary project in the University of Oxford on this question. The application site is below, and the closing date for applications is <strong>12.00 midday BST on 22 Jun 2018.</strong></p>
<p dir="auto"><a href="https://is.gd/sKcvDd" style="color:#3983C4">https://is.gd/sKcvDd</a></p>
<h2 style="font-size:1.2em">Postdoctoral Research Assistant in Machine Learning</h2>
<h3 style="font-size:1.1em">Department of Engineering Science, Oxford</h3>
<p dir="auto"><em>Grade 7: £31,604 - £34,520 .</em></p>
<p dir="auto">More details and applications here: <a href="https://is.gd/sKcvDd" style="color:#3983C4">https://is.gd/sKcvDd</a>.</p>
<p dir="auto">We are seeking a full-time Postdoctoral Research Assistant to join the machine learning research group at the Department of Engineering Science (central Oxford). The post is is fixed-term to 31 October 2019. The post will entail working on a project titled “Creative Algorithmic Intelligence: Capabilities and Complementarity”. Your role in the project is to develop novel probabilistic machine learning algorithms for data characterising creative tasks.</p>
<p dir="auto">Creativity has often been considered beyond the scope of algorithmic intelligence: however, recent years have produced striking examples of algorithms, that might be called creative, contributing to cultural production. Such examples include the algorithmic production of news, films and chamber music. This project will assess the scope of present and future capabilities of creative algorithmic intelligence, and to what degree these algorithms can be complementary to human creativity.</p>
<p dir="auto">The project represents an interdisciplinary collaboration with Professor Rebecca Eynon in the Oxford Internet Institute. The project will make use of mixed methods, using machine learning techniques underpinned by robust and rich qualitative data. Your responsibility is for algorithmic classification and modelling to study the complementarity of creative algorithmic intelligence to workplace tasks, and you will work closely with another postdoctoral team member based in the Oxford Internet Institute.</p>
<p dir="auto">You should hold a relevant PhD/DPhil or be near completion in engineering, computer science, mathematics, statistics, economics or similar, with specialisation in probabilistic models (with the possibility to underfill at Grade 6: £28,098 - £33,418 p.a. if the candidate holds a relevant degree/Masters and is working on PhD/DPhil) together with relevant experience;</p>
<p dir="auto">Informal enquiries may be addressed to Professor Michael Osborne at <a href="mailto:mosb@robots.ox.ac.uk" style="color:#3983C4">mosb@robots.ox.ac.uk</a>.</p>
<p dir="auto">Further information can be found at: <a href="http://www.eng.ox.ac.uk/jobs/home" style="color:#3983C4">www.eng.ox.ac.uk/jobs/home</a></p>
<p dir="auto">You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.</p>
<p dir="auto">Kindest<br>
Mike</p>
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<p dir="auto">Michael A Osborne:<br>
Dyson Associate Professor in Machine Learning, Engineering Science;<br>
Co-Director, Oxford Martin Programme on Technology and Employment;<br>
Co-Director, EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems; and<br>
Official Fellow, Exeter College.<br>
All are at the University of Oxford.<br>
+44 (0)1865 616622<br>
<a href="http://www.robots.ox.ac.uk/%7Emosb" style="color:#3983C4">http://www.robots.ox.ac.uk/~mosb</a><br>
<a href="http://twitter.com/maosbot" style="color:#3983C4">http://twitter.com/maosbot</a></p>
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