Connectionists: postdoc job in machine learning at the University of Oxford, deadline 23 Mar

[Michael A Osborne]

Come help understand how machine learning will transform employment in 
healthcare!

Best
Mike

__________________________________
Michael A Osborne
Dyson Associate Professor in Machine Learning, Engineering Science
Co-Director, Oxford Martin Programme on Technology and Employment
Faculty Member, Oxford-Man Institute of Quantitative Finance
Official Fellow, Exeter College
University of Oxford
+44 (0)1865 616622
http://www.robots.ox.ac.uk/~mosb
http://twitter.com/maosbot

## Postdoctoral Research Assistant in Machine Learning

### Department of Engineering Science, Oxford

*Grade 7: £31,076 - £38,183 p.a.*

More details and applications here: https://is.gd/i2mA7D. The closing 
date for applications is **12.00 midday on 23rd of March 2017.**

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 fixed-term to 31 May 2018. The post will 
involve work on a project funded by the Health Foundation.

Your role in the project is to develop novel probabilistic machine 
learning algorithms for economic data characterising the future of 
employment. The project examines automation and computerisation in UK 
primary healthcare delivery; the project’s website is here: 
http://healthautomation.oii.ox.ac.uk.

You should possess a good first degree in Engineering, Computer Science, 
Mathematics, Statistics, Economics or similar, with specialisation in 
probabilistic models and have or are about to complete a PhD in a 
relevant area. 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. Informal enquiries may be addressed to Prof Michael 
Osborne (email: mosb at robots.ox.ac.uk).

The department holds an Athena Swan Bronze award, highlighting its 
commitment to promoting women in Science, Engineering and Technology.

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