Computer Laboratory

Raspberry Pi

Raspberry Pi Summer Internship Programme (2013)

(All internships have now been allocated)

We are looking for approximately ten students to take part in a range of projects that make use of the Raspberry Pi computer. A list of projects can be found below.

Alternatively, if you have an interesting project idea of your own, please contact the programme organiser (Robert Mullins). The tutorials created by last year's summer students can be found here.

A few more details:

  • You must be a Cambridge Undergraduate NOT in your final year of study. Applications from students in all departments are very welcome
  • The placements last 10 weeks from the 24th June to 30th August
  • You will recieve a bursary of 400GBP/week to cover your accommodation and other expenses. To clarify, this placement is not classified as employment, rather it is a training opportunity to help you develop technical and transferable skills.
  • If you are interested in one of the projects below, please email the contact named. Alternatively, if you would like to propose a project, please email Robert Mullins.
  • While you will be based in your supervisor's department, we are planning a number of events to ensure that all of the summer interns are brought together during the programme.
  • A condition of taking part in the programme is that you agree to release any intellectual property that you develop whilst working on the programme into the public domain, i.e. you will be expected to write up you project and release text and code (under an appropriate FSF approved license).

If you have any questions please do not hesitate to contact Robert Mullins.


"Sensing and data logging with a Raspberry Pi"

Supervised by: Jim Haseloff (, Simone Hochgreb (, Alexandre Kabla (
Places available: 2-3
Requirements: Skills in programming and/or electronics

Sensing and monitoring of environmental parameters is ubiquitous in engineering. Typical systems in industry and labs include a sensor, a data conditioning module, and a personal computer or data logger to connect the signals to a readable output. Today, most smart phones have sufficient processing and memory capabilities to allow data acquisition for most common laboratory experiments. Yet we continue to use dedicated PCs and data acquisition boards at a high cost. We would like to offer projects aiming to create simple, low cost solutions to data acquisition and logging for most generic educational and laboratory purposes.

Students will work as a team and explore various technical approaches (using off-the-shelf solutions, interfacing with Arduino boards, or developing custom circuits) with delivery to local/remote dataloggers via different protocols. The production of detailed tutorials will represent an important part of the work.

Potential student projects within this theme:

  • Novel sensors and data acquisition with the RPi
  • High speed data transfer through SPI
  • Networked data logging

During this project the student will:

  • learn about sensing and data logging technologies
  • develop her/his team working skills
  • improve her/his communication skills by presenting results and generating public domain documentation

"Versatile imaging platform using a Raspberry Pi"

Supervised by: Jim Haseloff (, Simone Hochgreb (, Alexandre Kabla (
Places available: 2-3
Requirements: Skills in programming and/or optics

A large number of tasks in materials characterisation, biological analysis or medical diagnostics rely on the detection of specific features in images. Most applications do not require particularly high frame rates or resolutions and a webcam often provides sufficient image quality. Current professional software and off the shelf systems are costly. This creates an opportunity for developing inexpensive hardware and software solutions that may do the job just as well.

The Raspberry Pi and its new camera module offer fantastic opportunities to develop an open platform for imaging. Two students will work in concert to develop control software, optical components, and produce tutorials.

Potential student projects within this theme:

  • Image acquisition with the RPi - Software project using the new camera module of the Pi
  • RPi based table-top chassis for automated optical measurements.
  • RPi controller for environmental sensing and control of biological samples

During this project the student will:

  • learn about imaging, image processing and microscopy
  • develop her/his team working skills
  • improve her/his communication skills by presenting results and generating public domain documentation

"Building a lightweight RFID tag reader platform using Raspberry Pi by integrating OpenBeacon RFID USB reader"

Supervised by: Eiko Yoneki (
Places available: 1
Requirements: Good programming skills (C, C++), Linux and network configuration would be advantageous

This project aims to build a low-cost active RFID tag reader using the Raspberry Pi. The ultimate goal is to use the system, together with active RFID tags, to monitor mobility and interaction between people, e.g. in a research laboratory or hospital.

The ability to read active RFID tags will be provided by a OpenBeacon USB stick reader (part of the OpenBeacon platform) The overall functionality will be similar to that provided by the OpenBeacon Ethernet EasyReader PoE II. If time allows, a demonstrator system built from multiple readers will be deployed and tested.

This project aims to build upon the supervisor's previous work in this area carried out as part of the FluPhone project (BBC report)

"Adventures with Raspberry Pi"

Supervised by: Sam Aaron (, Alan Blackwell ( and Robert Mullins (
Places available: 4-5
Requirements: Familiarity with a mainstream programming language

We aim to develop a range of new programming tools and application demonstrators that will help bring Raspberry Pi to new audiences. You will work as a member of a team including other interns, PhD students, and post-doctoral researchers in arts, technology and education.

We are also keen to pursue interesting hardware/physical computing projects and extend the tutorials that were created last year. We would be very happy to suggest projects in these areas or to recieve short proposals from you.

You will be based at the Computer Laboratory for these projects where you will work alongside the other Raspberry Pi interns.