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IIP-Queen's University Belfast
Belfast, Northern Ireland (Outgoing Program)
Program Terms: Summer
This program is currently not accepting applications.
Partner Institution/Organization Homepage: Click to visit
Restrictions: Princeton applicants only
Fact Sheet:
Dept Offering Program: IIP, International Internship Program (IIP) Program Type: Internship
Language Prerequisite: No Degree Level: 2 First year Ugrad, 3 Sophomore, 4 Junior
Time Away: Summer Housing options: Student Responsibilty with support from IIP and/or Host Organization
Program Group: International Internship Program
Program Description:
Queen's University Belfast
About:
Queen's University Belfast is part of the prestigious Russell Group of the UK's 24 leading research intensive universities. Their world-class researchers carry out internationally leading research, with Queen's placed joint 8th in the UK for research intensity. The UK's ninth oldest university, Queen's was founded as Queen’s College in 1845, and can trace its roots as far back as 1810. With more 170 years of heritage, Queen's University Belfast combines an international reputation for academic excellence with a life-changing student experience and a culture of innovation. Queen's prides itself on the quality of its academic leadership, with a united team of academics and professional services directorates working together to deliver its Vision.

Intern Responsibilities: IIP interns will work on one or more of the following projects:
  • PROJECT 1:  Position control for EV wireless charging - As a clean transportation, electric vehicles are becoming increasingly popular. The charging of EV batteries is usually done through a plugged-in cable which is sometimes inconvenient. By contrast, wireless charging is much easier as it doesn’t involve any physical contact during the charging process. A car can be charged instantly once it is parked or on move. However, due the mechanism of wireless energy transmission, the energy transfer and receiver has to be properly aligned to achieve the maximum charging efficiency. 
In this project, PID controllers for three dimensional charging position control platform will be developed. This is based on an existing wireless charging platform. It is expected to implement the control algorithm through Raspberry Pi or Arduino controller.The objectives of the project are:
  1. Become familiar with DC motor and stepper motor control, and PID controller.
  2. Become familiar with embedded programming.
  3. Embed three dimensional motor PID controllers.
  4. Develop local and remote motor position control.
  5. Validate remote control through both PC and raspberry Pi.
  6. Evaluate the charging efficiency under different charging positions.
  • PROJECT 2:  Position control for EV wireless charging - With the resurgence in interest of VR (Virtual Reality) in recent years, largely due to new HMD (Head Mounted Display) technology, namely the Oculus Rift, HTC VIVE, Microsoft Hololens etc.  visual aspects of technological advancement far outpace that of the input or interaction technology. Currently there are no large scale haptic devices for use with VR, most haptic devices have very small working volumes; an exception to this is the use of gloves. However, haptic gloves do not provide full force feedback, more commonly it is vibro-tactical. As most force feedback haptic devices are at their core a robotic arm.
A solution to this is to use a larger robot, this has its own concerns, such as safety and cost. We believe that the Baxter Robot provides a middle ground to these, it has two 7-DOF arms mounted on a single torso, is designed with safety in mind and due to these safety features, it can be operated without a cage and in close proximity to the user. We propose using the Baxter robot as an encounter haptic device. Encounter haptic systems need a form of input as the user is not attached to the device or robotic arm for positional data, for this we propose using the Vice tracking controller, which can track a user’s hands in 6-DOF.

Specifically, the objectives of this project are:
  1. Research and become familiar with the Baxtor, Vive and latest developments in the areas of haptics and VR.
  2. Become familiar with the current working system of Vive and Baxtor for encounter haptics.
  3. Design and develop a piece of hardware that can be held by Baxtor to deliver different haptics experiences to the user.
  4. Develop suitable VR content to allow the user to interact with surfaces of different textures. 
Learning Outcomes: On completion of this project, you will have:
  1. A practical understanding of the Baxtor Robotic System and VR Vive device.
  2. A strong grasp of the behavior of tracking systems and haptics.
  3. A working knowledge of the performance/cost and trade-offs implicit in practical implementations and user testing.
  • PROJECT 3:  Making sense of cancer data via deep learning - This project aims to use computers to make sense of a large set of medical data relating to types of cancer. A medical scientist would love to see the entire big picture what has changed in the patient compared to a normal human being without cancer. But since that analysis tool is not available, he cherry picks the genes he is interested in, and compares tumour and normal tissue. Ultimately the research team wants to provide a better and more complete method using modern machine learning, such as deep learning.
The project will be suitable for a IIP intern with some computer programming experience and an interest in data science and/or life sciences. The project will be supervised for the duration of the internship.
  • PROJECT 4: Phase Estimation Algorithms for the “OpenPMU” Smart Grid sensor technology platform- Phasor Measurement Unit (PMU) technology has become a mainstream tool of the power systems engineer.  PMUs allow all manner of interesting phenomena to be analysed, from transmission system faults to power oscillations induced by wind farms. The OpenPMU project is concerned with the advancement of Phasor Measurement Unit technology for the purposes of academic research.  In this project, a Python program will be written to convert streaming sample data (representing substation voltage/current waveforms) into their phasor representations. The IIP intern will subsequently add state-of-the-art quality assessment functions, comparing the phasor created with the waveform data that produced it.  The IIP intern will be expected to communicate with research centres in USA/Sweden/Australia on this topic.
IIP candidates for this project should have a strong background in mathematics, and the ability to program in the Python language.  An interest in signal processing would be preferred.
  • PROJECT 5:  Memory system optimization of the Intel Xeon Phi Knights Landing - The organization of modern computers is becoming increasingly complex. One key component of computers, the memory system, has multiple levels of hardware caches. While hardware caches are typically oblivious to programmers (programmers typically do not think about how efficiently caches are used when writing software), the recently introduced Xeon Phi Knights Landing has an additional cache level that can be managed explicitly in software. This opens opportunities to significantly enhance the performance of the cache by using application-specific knowledge.
This project will explore software management of the die-stacked eDRAM cache of the Xeon Phi Knights Landing processor. The project will investigate stencil computations, a class of algorithms used widely in scientific computing to calculate how physical quantities such as heat and air pressure evolve over time. Such algorithms are predictable enough such that caches can be managed by software. The goal of the project is to explore policies and techniques to move data between the eDRAM cache and main memory in order to increase performance.  The aim is to outperform the standard, application-agnostic policy implemented in hardware. During this project, you will learn about software optimisation, the performance characteristics of memory systems such as memory locality and how they are affected by program structure.

PROJECT 6:  OpenCL machine - A p-code machine (pmachine) is a program which simulates the execution of a simple processor, typically providing basic arithmetic and control flow instructions (p-code). OpenCL is a programming approach/library which permits program functions (kernels) to be executed in parallel on accelerators such as GPUs. The purpose of this project is to investigate the use of a p-code machine running on a GPU to see whether good performance can be combined with some of the other benefits of this approach.

Qualifications: IIP candidates with interests in electrical engineering, computer science and mathematics are encouraged to apply. Technical skills in C/C++, Python and/or Open CL would be an asset.


Dates / Deadlines:
This program is not currently accepting applications. Please consult the sponsoring department's website for application open dates.
 
This program is currently not accepting applications.