Research Associate - Science of Science

The University of Manchester
Manchester
1 week ago
Create job alert

We seek to appoint a Research Associate in the Science of Science to work on the UK-DOCTRACK project. The researcher will be housed at the Manchester Institute of Innovation Research, Alliance Manchester Business School, under the supervision of Prof. Cornelia Lawson and Dr Xin Deng.

The Research Associate will undertake research as part of a team project that is creating a longitudinal database of UK PhD graduates that allows identifying their direct and indirect contribution to invention. The project is sponsored by the European Patent Office (EPO) and part of the wider DOCTRACK, led by Catalina Martinez (CSIC, Spain), a European wide effort to investigate the performances of PhDs and to create a new open European PhD database.

The project’s goal is investigate barriers to innovation along the pipeline, including gender biases, and to contribute insights to understand the constraints of economic growth in the UK. The project also seeks to understand career trajectories of doctoral graduates and the role of supervisors and new technologies in shaping these trajectories.

This 12 month position will support a scholar who seeks to develop leading-edge researchthat probes these questions using large-scale advanced quantitative bibliometrics, patent analytics, and modelling.The researcher will also have the opportunity to suggest their own research ideas.

The successful candidate will have a commitment to research and publication and to methodological advancement. We welcome applicants from doctoral graduates, early career researchers, and others for whom this one-year position is suitable. The position is open to applicants from diverse educational backgrounds, includingmanagement, economics, social science, information science, and computer science.Applicants who combine disciplines, for example sciences or engineering at the undergraduate level with social sciences at the doctoral level are encouraged to consider this opportunity. We will also consider candidates with other combinations of qualifications. However, applicants should have a strong record in quantitative methodological research skills, desirably including experience with bibliometric, patent or other big data sets, text mining, large language models, machine learning, and experience or an interest in applications to science.

The Manchester Institute of Innovation Research is a world leading centre for the study of science and innovation policy and management. Our 45 members of staff and 30 doctoral students build on more than five decades of interdisciplinary science, technology and innovation studies in Manchester. Our research, teaching and engagement activities are based upon a guiding principle of excellence, both in terms of academic rigour and societal relevance. The successful candidate will be associated with the Institute’s Emerging Technologies and Governance and its Science, Technology and Innovation Policy research themes.

The Alliance Manchester Business School is one of the world’s leading business schools, ranked 2nd in the UK for research power.

The University of Manchester enjoys a reputation for ground-breaking research and innovation. We are located in the heart of Manchester and the Oxford Road Innovation District.

In the Additional Information section of the application form, please include discussion of your capabilities, experience including required and desirable methodological skills, interests related to the science of science, science practices, and your own proposed research theme.

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 support an inclusive working environment and welcome applicants from all sections of the community regardless of age, disability, ethnicity, gender, gender expression, religion or belief, sex, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working you can find out morehere

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: Prof. Cornelia Lawson and Dr Xin Deng

Email: and

General enquiries:

Email:

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.


Related Jobs

View all jobs

Research Associate in Bioinformatics and Data Science

Research Associate Programmer in EGENES

Research Associate/Senior Research Associate - City Futures Research Centre

Research Associate/Senior Research Associate - City Futures Research Centre

Research Associate/Senior Research Associate - City Futures Research Centre

Research Associate/Senior Research Associate - City Futures Research Centre

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.