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Position: Research Fellow/Senior Research Fellow - Artificial Intelligence in Ophthalmology
Institution: University College London
Department: Institute of Ophthalmology
Location: London, United Kingdom
Duties: This will be a joint appointment between UCL Institute of Ophthalmology (IoO) and the UCL Centre for Medical Image Computing (CMIC) within the UCL Department of Computer Science. The main duties will be the development of novel artificial intelligence models for ophthalmology, in particular exploring methods to provide clinical interpretability for such models. The post-holder will also explore topics such as generalizability of machine learning models, out-of-distribution detection, and probabilistic segmentation of ophthalmic images
Requirements: The applicant is required to have an honours degree (minimum 2: 1) and a PhD in a discipline related to this project (mathematics, statistics, engineering or physics), and a track record in machine learning applied to large-scale data analysis. The applicant should also have excellent communication skills and a commitment to conducting high-quality research that will benefit healthcare; Essential requirements for appointment at grade 8 include experience with deep learning and relevant computational tools (e.g. PyTorch) and teaching and supervising students
   
Text: Research Fellow / Senior Research Fellow - Artificial Intelligence in Ophthalmology, - Ref:1878661 Click here to go back to search results Apply Now UCL Department / Division Institute of Ophthalmology Location of position London Grades 7-8 Hours Full Time Salary (inclusive of London allowance) Grade 7 £36,028 - £43,533 Grade 8 £44,737 Per Annum Duties and Responsibilities This will be a joint appointment between UCL Institute of Ophthalmology (IoO) and the UCL Centre for Medical Image Computing (CMIC) within the UCL Department of Computer Science. The main duties will be the development of novel artificial intelligence models for ophthalmology, in particular exploring methods to provide clinical interpretability for such models. The post-holder will also explore topics such as generalizability of machine learning models, out-of-distribution detection, and probabilistic segmentation of ophthalmic images. Previous applicants need not re-apply, and the post will be available till 31st March 2023 in the first instance. Key Requirements The applicant is required to have an honours degree (minimum 2:1) and a PhD in a discipline related to this project (mathematics, statistics, engineering or physics), and a track record in machine learning applied to large-scale data analysis. The applicant should also have excellent communication skills and a commitment to conducting high-quality research that will benefit healthcare. Essential requirements for appointment at grade 8 include experience with deep learning and relevant computational tools (e.g. PyTorch) and teaching and supervising students. Further Details A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the 'Apply Now' button below. Please ensure you attach your CV and list of publications. You should also provide a personal statement to support your application. If you have any queries regarding the vacancy please contact Dr Pearse Keane (email: p.keane@ucl.ac.uk) or Professor Daniel Alexander (email: d.alexander@ucl.ac.uk). If you have any queries regarding the application process please email hr.ioo@ucl.ac.uk. We particularly welcome female applicants and those from an ethnic minority, as they are under-represented within UCL at this level. UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 14 Sep 2021 Latest time for the submission of applications 23.59 hours Interview date tbc Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. JD 1878661 Apply Now
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