CMIT Summer Research Internship 2025

-------------- Deep Learning for Mathematical Imaging ---------------

Started in 2019, we will continue again this year the successful series of CMIT summer research internships. The internship is open for all Maths UG students (primarily year-1 and year-2 students, but also year-3 students are welcome) who are interested in data science and optimization problems and would like to gain hands-on research experience with cutting edge deep learning techniques. Candidates should ideally have some Python or Matlab experience, some background in data science is a plus but not required. We arrange for several training courses at the start of the internship.

For info, in 2022, about 30 students started the Part 1 courses and 12 have finished a project in Part 2 (including two placed in City University of HK); the latter received a CMIT certificate. A short summary of the 2023 and 2024 editions can be found here and here.

The internship will run in the time between June and August 2025. For each participant, a minimum, but flexible, time commitment of 4 weeks is expected in addition to taking part in the online lectures (unless you are fluent with PyTorch and TensorFlow). One student, based on interest and academic performance, will have the opportunity to participate in the City University of Hong Kong Summer Internship (Exchange) scheme.

Application form (Word) and PDF form.

Interested candidates should submit the application form in any format (either Word or PDF), before 9th March 2025, by email
with the SUBJECT TITLE "CMIT internship application" to   andreas.alpers@liverpool.ac.uk

However application for City University of Hong Kong Summer Internship (exchange) must be be submitted before 30th Jan 2025 to meet the CityU deadline 1 Feb with acceptance announced on 31st Jan. Decisions on acceptance will be made within a week of 9 March 2025. Interviews to decide who is working on which of the projects will be held after the first part, the online lectures, concluded.

Best wishes

Dr. Andreas Alpers (University of Liverpool) and Prof. Ke Chen (Strathclyde).