About us
UCL established the Institute of Health Informatics (IHI) in August 2014 and is part of the UCL Faculty of Population Health Sciences.
Institute of Health Informatics conducts high quality data-intensive research to improve health at local, national and international levels and delivers one of the largest and most highly regarded teaching programmes in health informatics and health data science. It is home to one of four UKRI Centres for Doctoral Training in AI in Healthcare.
About the role
Institute of Health Informatics is looking to appoint a Part time (0.50 FTE) Research Fellow in Generative AI in Health to join our welcoming and vibrant Institute.
This position presents a unique opportunity to join a team of experienced health data scientists, informaticians, statisticians and clinical epidemiologists and contribute significantly to the statistical analysis and subsequent presentation of results from large scale national and rich local health record data resources. The Research Fellow in Generative AI in Health will conduct research on text analytics and knowledge-driven methods, focusing on public health and healthcare datasets.
Duties include creating a framework for analysis of user/patient feedback and identifying algorithmic bias. The Fellow will engage with project members and support the delivery of the research programme.
The post is funded until 31 January 2028, further funding may become av ailable.
The salary for this position will be £42,099 - £50,585 pro rata, per annum.
Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at research assistant Grade 6B (salary £33,619 - £36,348 pro rata, per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.
This role does not meet the eligibility requirements for a Skilled Worker certificate of sponsorship under UK Visas and Immigration legislation. Therefore UCL will not be able to sponsor individuals who require right to work in the UK to carry out this role.
For an informal discussion please contact Paulina Bondaronek [email protected]
For any queries regarding the recruitment process please contact Anita Gorasia [email protected]
About you
If you believe you meet the requirements why not come and be part of this unique and exciting opportunity and be part of something where you feel included, valued and proud.
The Research Fellow in Generative AI in Health must have a PhD in computer science, informatics, or a related discipline, as well as excellent skills in natural language processing and machine learning. They should have experience with large-scale datasets and a strong understanding of Explainable AI principles.
What we offer
We will consider applicates to work on a part-time, flexible and job share wherever possible.
As well as the exciting opportunities this role presents, we also offer some great benefits some of which are:, 41 Days holiday (pro rata for part time staff) (27 days annual leave 8 bank holiday and 6 closure days), cycle to work scheme, season ticket loan, on-site gym and employee assistance programme
Visit https://www.ucl.ac.uk/work-at-ucl/ reward-and-benefits to find out more.
Our commitment to Equality, Diversity and Inclusion
The Institute prides itself on operating in an all-inclusive environment irrespective of personal, physical, or social characteristics.
As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.
We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.
You can read more about our commitment to Equality, Diversity and Inclusion here
https://www.ucl.ac.uk/equality-diversity-inclusion/
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