Researcher positions in probabilistic machine learning: Research Fellow, Postdoc and PhD Student

The International Society for Bayesian Analysis
Manchester
16 hours ago
Applications closed

Related Jobs

View all jobs

Baseball Analyst / Data Scientist

Lecturer (Teaching and Scholarship) in Music and Data Science

Lecturer / Senior Lecturer in Artificial Intelligence (Machine Learning, NLP, Reinforcement Lea[...]

Specialist Machine Learning Researcher

Data Science Lead — Hybrid Kidney Research

Data science programme lead

Researcher positions in probabilistic machine learning: Research Fellow, Postdoc and PhD Student

Manchester Centre for AI Fundamentals has researcher positions open at several levels: Research Fellow, Postdoc and Postgraduate Research Student (funded). DL June 30, 2022

I am hiring researchers to my team working on probabilistic machine learning. Keywords include: Bayesian inference, reinforcement learning and inverse reinforcement learning, automatic experimental design, multi-agent learning, Bayesian deep learning, amortized inference, human-in-the-loop learning, user modelling, collaborative AI, privacy-preserving learning, likelihood-free inference. Different researchers work on different but related subsets of these. The work is funded by UKRI Turing AI World-Leading Researcher Fellowship programme, on “Steering AI in Experimental Design and Decision-Making”.

The team is based in the new Manchester Centre for AI Fundamentals, which builds on the new ELLIS Unit Manchester and the Alan Turing Institute. In addition to these outstanding AI and Machine Learning collaboration opportunities, we collaborate with excellent teams in other fields, in both academia and industry, which give application opportunities for those interested: personalized medicine, especially for cancer and remote medicine; synthetic biology; digital twins more generally, etc.

Now is the time to join the University of Manchester when it is significantly boosting its activities in Machine Learning!


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.