A fully funded PhD studentship is immediately available within the School of Engineering and Physical Sciences at Heriot-Watt University in conjunction with ARM Ltd. The research will be targeted at adaptive automatic assessment for engineering education and training and will focus on supporting on-line training materials. The successful candidate will be provided with funding to pay tuition fees and a tax-free maintenance stipend for 4 years.
Conventional summative and formative assessment methods, relying heavily on human intervention, do not scale up readily to the needs of mass-participation on-line education and training in, for example massive open on-line courses (MOOCs). This project seeks to develop and demonstrate ways in which significant parts of such assessment can be handled automatically by adaptive software tools that harness the most recent advances in machine learning. Embedded systems design and programming, using ARM development tools, will be used as a demonstrator area with ARM’s latest educational and professional training programs as test vehicles. The resulting tools will be tested through large worldwide field trials. If successful, the work will be expanded to other areas of education.
We are seeking a talented, creative, proactive, and strongly motivated individual to work on a new ground-breaking project with the potential for publications in high impact journals. Suitable applicants will have a good first degree in Computer Science Electrical and Electronic Engineering or other relevant subject in engineering or the physical sciences. Only candidates with good communication skills in English, including oral and written language are encouraged to apply.
Key requirements include -
• Good programming skills in C/C++ or equivalent
• Experience in machine learning and web technologies is desirable
• Experience in embedded systems’ design and programming is desirable
The selected student will be based at the School of Engineering and Physical Sciences at Heriot-Watt University in Edinburgh. They will also work for periods of a week at a time, typically four times per year, at ARM in Cambridge (travel and accommodation provided). There will be opportunities to travel to conferences and other events for collaboration and dissemination purposes.
How to apply
In the first instance applications should consist of a cover letter and a CV containing a detailed description of the candidate’s most relevant experiences and expertise in the fields of computer-based learning, machine learning and/or microcontroller applications and technology. A brief paragraph about the candidate’s extracurricular activities is also welcome.
All documents should be sent to Dr Donald Reay ([email protected]