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Graduate Researcher in Human-AI Interaction

University of Oxford - Department of Experimental Psychology

Location: Oxford
Salary: £34,982 to £40,855 p.a : Grade 6
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 17th March 2025
Closes: 31st March 2025
Job Ref: 178671

The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence.  Our research plays a key role in tackling many global challenges, from reducing our carbon emissions to developing vaccines during a pandemic.

Currently located in the Radcliffe Observatory Quarter, Experimental Psychology will be moving to the new, purpose-built Life and Mind Building (Home | The Life and Mind Building (ox.ac.uk)) a multidisciplinary research and teaching facility due to open in the summer of 2025. 

We are seeking a motivated and talented researcher experienced in human-AI interaction to join a research team focussed on studying learning and decision-making in humans and machine learning systems. The Human Information Processing (HIP) Lab is headed by Prof Christopher Summerfield.

The post is funded by the Wellcome Trust for two years and is offered on a full time basis.

The role will involve a range of activities including responsibility for carrying out rigorous and impactful research building machine learning models; design, analyse and conduct computational simulations; provide guidance in machine learning methods to others in the group where necessary; and independently manage academic and associated administrative duties to coordinate workload to meet deadlines.

You will hold a BSc (and ideally MSc) in a quantitative field such as statistics, computer science, physics, or computational neuroscience / cognitive science with excellent organisational skills and the ability to manage priorities and resources.  Experience in researching humans and machine learning models; strong quantitative, programming and analytical skills; and proven track record of publishing work in this field are essential criteria for this role.

Applications for this vacancy are to be made online.  You will be required to upload a supporting statement, CV and the details of two referees as part of your application.

Only applications received before 12:00 midday on 31st March 2025 will be considered.

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