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Research Associate in Multimodal Artificial Intelligence for Biology

The University of Manchester

Manchester

Hybrid

GBP 30,000 - 40,000

Full time

Yesterday
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Job summary

The University of Manchester invites applications for the Postgraduate Research Associate position in Multimodal Artificial Intelligence for Biology. This role offers an opportunity to advance machine learning methods in cancer research, requiring a PhD or MSc and an interest in biology, along with a strong publication record. Competitive salary, excellent benefits, and a commitment to diversity and flexibility are provided.

Benefits

Market leading Pension scheme
Employee Assistance Programme
Generous annual leave
Paid closure over Christmas
Discounts at major retailers

Qualifications

  • Strong interest in biology and health is essential.
  • Good scientific publication record expected.
  • Self-motivated and able to work in an interdisciplinary team.

Responsibilities

  • Contribute to the development of multimodal machine learning methods.
  • Predict spatial organization of tumor microenvironment using integrated data.

Skills

Machine Learning
Integration of Multimodal Biological Data
Artificial Intelligence
Research Skills

Education

PhD or MSc with Machine Learning element

Job description

Applicants are invited for the post of Postgraduate Research Associate in Multimodal Artificial Intelligence for Biology.

The aim of this interdisciplinary project is to establish that routinely collected histological images can serve as a cost-effective proxy for expensive spatial molecular profiling in brain tumour.

The post-holder will contribute to the development of multimodal machine learning methods that integrate multiple spatial omics layers with histology and clinical data to predict the spatial organisation of the tumour microenvironment in brain tumours. This position offers an exciting opportunity to work at the intersection of multimodal AI, cancer biology and digital pathology.

The successful applicant will have a PhD or MSc with a significant machine learning element and/or experience with integrating multimodal biological/health data. A strong interest in biology and health is essential.

The candidate should have a good scientific publication record given career state and be self-motivated, hard-working and able to work in an interdisciplinary team.

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
The School is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. An appointment will always be made on merit. For further information, please visit: https://www.bmh.manchester.ac.uk/about/equality/

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 recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk .

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

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr Sokratia Georgaka

Email: sokratia.georgaka@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

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.
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