** APPLICATIONS HAVE NOW CLOSED**
Apply now for a Summer 2023 internship - project details below.
The Distributed Algorithms CDT, together with the Signal Processing Group, host Summer Internships each year and are looking for keen and conscientious students to join us during the Summer periods for an 8-10-week programme. Applications are being accepted for the 2023 programme.
Interns are supervised by and collaborate with current CDT postgrad researchers, a senior researcher lead, the wider research group, and external partners.
Data Gathering and Tracking: Bus Open Data Service
Supervisors: Josh Murphy and Yiyi Whitechelo (and Dr Lee Devlin, Lecturer)
The UK Bus Open Data Service (BODS) provides bus timetable, vehicle location and fares data for every local bus service in England. However, BODS only provides live location data which makes it difficult to batch-train tracking algorithms. While some solutions to exist, like BODS data extractor, a python library which pulls down timetable data, there is no complete solution, particularly for historical location data.
The aim of this project is to scrape the timetable data and set up a means of scraping the location data which can be allowed to run until sufficient data has been gathered over a period of (2-3 months).
The focus of the internship is on the student experience and the development of knowledge and skills. You will be involved in activities, which will provide a valuable and meaningful experience, with tasks and activities carefully defined to fit the duration of the placement. These activities will be discussed at the intern induction and set out in a clear schedule of tasks and intended outcomes.
The successful applicant will have the opportunity to take on a project working with real-world data under some supervision but with plenty of scope to shape the direction and outcomes of the project. Working as part of the Distributed Algorithms CDT and the wider Signal Processing research group, they will be able to build their network and experience the research environment.
The student will be able to develop their data gathering, scraping and cleaning abilities in the Pandas, BeautifulSoup and Requests python libraries or whichever tools they find most appropriate for the task. An introduction to tracking algorithms will also be provided.
The student will learn about some elements of spatial plotting and spatial plotting tools and potentially how to run particle filters if they’re able to quickly accomplish the primary goals of the internship.
Please speak to the project supervisors (contact details at the end of this document) if you are unsure or would like more detail.
The plan is for the internship project to start 19th June 2023 and run for up to 10 weeks. The length of the internship is equivalent to 200 hours of activity which may be arranged to suit the needs of both the student and supervisors. For example, activity may be spread over a longer period of time or the intern can agree to work consecutive days for a shorter period. The specific arrangements will be made once a successful applicant has been appointed.
The successful applicant will be employed as an intern and receive a payment rate equivalent to the National Living Wage for a period of up to ten weeks. Payments will be made in arrears based on the number of hours worked.
Next steps and timescales
1. Applications will undergo independent assessments based on the following criteria:
- The skills, experience and knowledge that align with the project
- Interest in working with a research group
- The applicant’s intended outcomes
2. Candidates will be selected for a short, informal interview to discuss their application and interest in the internship. Interviews will be held 23rd May 2023 (or a date that suits the candidate).
3. Offers made 25th May 2023.
4. Start date 19th June 2023.
If you have any questions please contact the project co-supervisors.
Internship Supervisory Arrangement
Summer interns will join the Signal Processing Group, which is led by Simon Maskell, and has a growing portfolio of PhD students (39), post-doc research assistants (10), data scientists (7) and academics (5). Moreover, interns will be integrated into a pre-existing research subgroup where members of these subgroups have a specific focus but have common research interests.
Each subgroup meets for one hour every week and members of the team update each other on their progress and ask questions about their research. At the beginning of the project, supervisors will provide an overview of the previous research undertaken in the group that is relevant to this project and will direct you to initial reading material. Following this, you will have regular meetings with the supervisors of the project. Supervisors can also be contacted via email, teams or MS Teams at any time. You will also spend time at the CDT offices working with others and learning together.
Interns can benefit from training programs being run as part of the CDT in Distributed Algorithms. In addition to technical training, interns will gain valuable work experience and become a core member of one of the signal processing research subgroups. As a member of a subgroup, the interns will be invited to weekly meetings where they will provide updates on their progress and gain insight to research being undertaken in the subgroup. Throughout the internship, successful candidates will be exposed to a variety of academic, industrial and governmental researchers from a variety of disciplines.
This experience provides invaluable insight into the life of postgraduate research and would be a welcome addition to any CV. Moreover, the project exposes state of the art techniques in high-performance/distributed computing, machine learning and artificial intelligence.
Working as a summer intern proved to be a pivotal point in my career as a researcher. It was a unique opportunity to experience first-hand a professional research environment and helped me develop invaluable skills in the process. Even more importantly, once my internship finished, I was offered the PhD studentship that enabled me to pursue a PhD in the field that I loved and paved the way for my current position as a PDRA.Lyudmil Vladimirov, former intern & current postdoctoral researcher