Research Associate OR Research Fellow In Machine Learning

The University of Manchester; Manchester; Hybrid; GBP 35,000 - 55,000; Full time

Job summary

Join a forward-thinking institution as a Research Associate or Fellow in Machine Learning. You will collaborate with a team of AI researchers to develop innovative principles and methods that address novel challenges in the field. This role offers the opportunity to work on groundbreaking projects that can significantly impact scientific research. With a focus on user modelling and decision-making, you will contribute to the advancement of AI techniques in a supportive and flexible work environment. Enjoy a competitive salary, generous benefits, and the chance to make a difference in the world of AI.

Benefits

Market-leading pension scheme

Employee health and wellbeing services

Generous annual leave entitlement

Additional paid closure over Christmas

Discounts at major retailers

Qualifications

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

Responsibilities

• Develop new principles and methods for advanced user modelling.
• Work on projects involving machine learning and decision making.

Skills

Machine Learning

Bayesian Inference

Reinforcement Learning

Experimental Design

User Modelling

Education

PhD in relevant discipline

Job description

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 that inspires new problems in fundamental ML work and enables tackling new applications that can make a difference, such as in scientific research. The team has diverse expertise, allowing them 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, focusing on developing new principles and methods for advanced user modelling, sequential decision making, and automatic experimental design, with and without human-in-the-loop involvement.

Requirements:

1. A PhD (or equivalent) in a relevant discipline.
2. Excellent organisational skills.
3. The ability to work well both in a team and independently.
4. Experience with research methods and techniques within established research programmes.

What you will get in return:

• Market-leading pension scheme
• Employee health and wellbeing services, including an Employee Assistance Programme
• Generous annual leave entitlement plus bank holidays
• Additional paid closure over Christmas
• Discounts at major retailers

We are an equal opportunities employer welcoming applicants from all backgrounds regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation, and transgender status. All appointments are made on merit.

Our university supports flexible working arrangements, including potential hybrid working.

Please note:

• We cannot respond to enquiries or accept CVs/applications from recruitment agencies.
• CVs submitted by agencies will be considered a gift.

For enquiries about the vacancy, contact:
Name: Isabel Machado
Email: [e-mail]

For general enquiries:
Email: [e-mail]

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

This vacancy closes at midnight on the specified closing date.

See the link below for the Further Particulars document containing the person specification criteria.