Janeway Institute Postdoctoral Research Fellowship (Research Assistant or Research Associate) (Fixed Term)

University of Cambridge
Cambridge
1 year ago
Applications closed

The Faculty of Economics, Cambridge University has a Postdoctoral Research Fellowship available for candidates working in Empirical Analysis of Financial Markets who have recently been awarded a doctoral degree or expect to receive their degree by September 2025. The Fellowship is for a period of 3 years.

The Fellowship will be based at the Janeway Institute. The Janeway Institute was created to develop new fundamental ideas, methods and research which push the frontier of economics.

We welcome applications from researchers working on areas related to the below theme of the Institute (a non-exclusive list of topics of interest is in parenthesis)

Empirical analysis of financial markets (including high dimensional econometrics; high-frequency trading and market-microstructure; big data)

For more information see ().

Successful candidates should demonstrate an ability to develop their own research ideas and indicate how they can contribute to the empirical analysis of financial markets research group in Cambridge. It is expected that successful candidates' work will be at the cutting edge of the research frontier with a view to future publications in world leading journals.

Successful candidates who have not yet received their PhD by September 2025 will be employed on University Grade 5 as Research Assistants, starting at £31,396 per annum. Upon being awarded their PhD, their salary will be upgraded to Grade 7 as Research Associates (Fellowships), starting at £36,024 per annum in the first year. In the second year, the salary will rise to £37,099, and in the third year, it will be £38,205.

Limited teaching opportunities through the Janeway Teaching Fellowships are potentially available for those interested in gaining valuable experience and contributing to the learning environment. These opportunities are contingent on the Faculty's needs and the candidate being suitably qualified and eligible for the fellowship scheme. Further details, including additional remuneration for these teaching responsibilities, can be discussed during the interview process. Fellows would also have the possibility of joining a college.

Applications should consist of:a curriculum vitae;expression of interest cover letter outlining how you would be able to contribute to Janeway Institute in light of your research interests; job market paper;supplementary material containing other available research papers.

Three references will be sought upon receipt of application.

Queries may be directed to Marion Reusch, Janeway Institute Administrator,

Closing date: 15th December 2024

Interviews will be held in January or February.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.