Research Associate in Artificial Intelligence and Digital Twins

21 Feb 2024
Job Information

Organisation/Company

Liverpool John Moores University

Department

Computer Science and Mathematics

Research Field

Computer science » Other
Mathematics » Applied mathematics
Medical sciences » Health sciences

Researcher Profile

Recognised Researcher (R2)

Country

United Kingdom

Application Deadline

18 Mar 2024 - 23:59 (Europe/London)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

35

Is the job funded through the EU Research Framework Programme?

HE

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Liverpool John Moores University (LJMU) is a distinctive, unique institution, rooted in the Liverpool City Region and with a global presence. Our students and staff, past, present, and future, are the beating heart of our city and can be found in every corner of every industry and community. We couldn’t exist anywhere else and have shaped the city in which we belong. Working with the people of Liverpool to improve lives and support communities is at the heart of why we were founded and why we exist today.

To work within the EU TARGET project (https://target-horizon.eu/ ), to undertake research, conducting and recording the outcome of experiments and conducting literature and database surveys. To contribute to the analysis and presentation of results to internal/external audiences.

This research position will support the delivery of the EU Project TARGET: “Health virtual twins for the personalised management of stroke related to atrial fibrillation”. TARGET is a €10m Horizon Europe grant for a data science project on virtual twins (a.k.a. digital twins). TARGET’s consortium brings together the diverse expertise of leading academic institutions in 10 countries (Austria, Belgium, France, Germany, Greece, The Netherlands, Romania, Spain, Sweden, and the UK). It is composed of 19 partners, representing 8 academic partners, 6 hospitals, 4 companies and 1 charity.

LJMU is the leader of this multi-national EU project. TARGET’s ambition is to develop novel AI-based personalised, integrated, multi-scale computational models (virtual twins) and decision-support tools for the disease pathway of stroke related to atrial fibrillation, starting from the healthy state, pathophysiology and disease onset, progression, treatment and recovery. The project aims to help prevent AF and AF-related stroke, optimise acute management and rehabilitation, reduce long-term disability, provide a better quality of life for patients and caregivers, and lower healthcare costs.

In return, we offer an excellent benefits package including generous annual leave entitlement, pension scheme, induction and development support as well as family-friendly policies.

This is an exciting time to join the university as we deliver the LJMU Strategy 2030 and its vision of LJMU as an inclusive civic university transforming lives and futures, by placing students at the heart of everything we do.

If you feel that this is the role you have been looking for and your skills and experience can make a real difference at LJMU, we look forward to hearing from you.

LJMU is an equal opportunities employer and welcomes applicants from all backgrounds and communities irrespective of age, transgender status, disability, gender, sexual orientation, ethnicity and religion or belief.  All our appointments are made on merit.

Please note all of our vacancies will be closed to applications at midnight on the advertised closing date, unless otherwise stated.

LJMU are committed to adhering to the Principles set out in the Researcher Development Concordat; in line with this all fixed-term researchers will be supported to complete 10 days professional development activities per year (pro-rata). 

Requirements

Research Field

Computer science

Education Level

PhD or equivalent

Research Field

Mathematics » Applied mathematics

Education Level

PhD or equivalent

Research Field

Engineering » Computer engineering

Education Level

PhD or equivalent

Skills/Qualifications

Essential Factors	Evidence
Qualifications
PhD or equivalent experience in Artificial Intelligence, Computer Science, Mathematics or related subject	A
Experience and Knowledge
Detailed understanding, knowledge and programming of machine learning algorithms	A/I
Experience in conducting high-quality research involving machine learning	A/I
Experience in publishing high-quality academic peer-reviewed articles	A/I
Good knowledge of Python/R or similar	A/I
Abilities and Skills
Effective communication skills to convey complex information to a variety of audiences	A/I/P
Be able to demonstrate good interpersonal, time-management and organisational skills	A/I
A self-starter, able to work independently as well as part of a team	A/I
Ability to operate flexibly and reliably, adapting to change as required	A/I
Able to develop and maintain effective working relationships at all levels	A/I

 

Desirable Factors	Evidence
Experience and Knowledge
Proficiency in Python	A/I
Experience in working with large healthcare databases	A/I
Knowledge of the processes involved in preparing and submitting research funding proposals	A/I
Abilities and Skills
Strong communication skills with the ability to work in a multi-disciplinary research team, in a collegiate manner	A/I/P

A=Application Form     I=Interview     P=Presentation   R=Reference

 

Languages

ENGLISH

Level

Excellent

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

Liverpool John Moores University

Country

United Kingdom

City

Liverpool

Postal Code

L3 3AF

Street

James Parsons Building / Byrom Street

Geofield

Where to apply

Website

https://jobs.ljmu.ac.uk/vacancy/research-associate-3-years-fixed-term-with-the-…

Contact

City

Liverpool

Website

https://target-horizon.eu/
https://www.ljmu.ac.uk/

Street

James Parsons Building / Byrom Street

Postal Code

L3 3AF

E-Mail

[email protected]

Phone

+441512312155

STATUS: EXPIRED