Research Associate OR Research Fellow In Machine Learning

The University of Manchester; Manchester; Hybrid; GBP 40,000 - 70,000; Full time

Job summary

An established industry player invites applications for a Research Associate or Fellow in Machine Learning. This role offers a unique opportunity to collaborate with AI researchers on groundbreaking projects that impact scientific research. You will be part of a dynamic team focusing on innovative topics such as Bayesian inference and human-in-the-loop learning. The position promises a stimulating work environment, excellent benefits, and the chance to contribute to pioneering advancements in machine learning. If you are passionate about AI and eager to make a difference, this is the perfect opportunity for you.

Benefits

Market leading Pension scheme

Employee Assistance Programme

Exceptional annual leave entitlement

Paid closure over Christmas

Local and national discounts at retailers

Qualifications

• PhD or equivalent in a relevant discipline is required.
• Experience in research methods and techniques is essential.

Responsibilities

• Develop new collaborative AI principles and methods.
• Work on advanced user modelling and sequential decision-making.

Skills

Machine Learning

Bayesian Inference

Human-in-the-loop Learning

Reinforcement Learning

Automatic Experimental Design

Education

PhD in a relevant discipline

Job description

Research Associate OR Research Fellow In Machine Learning

Join to apply for the Research Associate OR Research Fellow In Machine Learning role at The University of Manchester

Research Associate OR Research Fellow In Machine Learning

Join to apply for the Research Associate OR Research Fellow In Machine Learning role at The University of Manchester

Applicants are invited for the posts of Research Associate or Research Fellow in Machine Learning to work with AI Researchers in the Centre for AI Fundamentals at the University of Manchester.

You will join a team of probabilistic modellers and machine learning researchers developing new collaborative AI principles and methods. This is an exciting topic which inspires new problems in fundamental ML work, and allows attacking new applications which make a difference, for instance in scientific research. Different team members have different expertise, and by working together are able to address more novel problems. Keywords include: automatic experimental design, Bayesian inference, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, computational rationality and user modelling, and simulator-based inference.

The post-holder will work on a project from Professor Kaski’s UKRI Turing AI World-Leading Fellowship. Research here includes work to develop new principles and methods for Advanced User Modelling, sequential decision making and Automatic Experimental Design, with and without a Human-in-the-Loop.

A PhD (or equivalent) in a relevant discipline is required. You should have excellent organisational skills and the ability to work well both in a team and using your own initiative. Experience in research methods and techniques to work within established research programmes is essential.

What you will get in return:

• Fantastic market leading Pension scheme
• Excellent employee health and wellbeing services including an Employee Assistance Programme
• Exceptional starting annual leave entitlement, plus bank holidays
• Additional paid closure over the Christmas period
• Local and national discounts at a range of major retailers
  
  
  

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working – you can find out more here

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any CV’s submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Isabel Machado

Email: [e-mail]

General enquiries:

Email: [e-mail]

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Other

• Industries

  Higher Education

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