This is a great opportunity for an individual who is confident with data processing and machine learning procedures. You will gain some valuable practical experience within the field of wireless communications and artificial intelligence. You will be mentored throughout this internship and will assist in the development of machine learning algorithms that will help minimise delays in cellular networks.

• Programming skills:  Python (required) and MATLAB (desirable)
• Solve difficult problems.
• Work with lots of data.

Other desirable criteria include:

• Working towards a Master’s degree in a highly quantitative field.
• Final year student. 
• Experience in Machine learning or statistics to solve real-world problems.

Dr Nidhi Simmons

This role will be an integral part of an exciting and innovative EU-funded project entitled “Smart-Edu4.0” in the creation of “A Trans-National Smart Manufacturing Education Hub” comprising UK and European institutions focusing on advancing Industry 4.0 educational activities at all institutions involved in the programme. This will be achieved through the design of industry-attuned and accredited new curricula and adaptation of existing curricula for undergraduate, postgraduate, and continuous professional development (CPD) training programmes, and the development of bespoke CPD leadership programmes to support Industry 4.0 champions within companies.

The intern will work within the Energy, Power and Intelligent Control research cluster as well as the Centre for Intelligent Autonomous Manufacturing Systems (iAMS) within the School of Electronics, Electrical Engineering and Computer Science. i-AMS is an interdisciplinary research centre spanning disciplines of Engineering, Computer Science, Applied Mathematics and Psychology working together to develop innovative technologies and solutions to address the challenges of Industry 4.0. iAMS at QUB is leading the management and delivery of the Smart-Edu4.0 project and will also lead the design of curricula with partners. iAMS will also investigate the feasibility and development of joint undergraduate and postgraduate programmes in Manufacturing Mechatronics with partner institutions with direct input from global manufacturing knowledge.

Embedding the two core concepts of Industry 4.0, namely Cyber-Physical Systems and Internet of Things, Smart-Edu4.0 will enable all stakeholders to visualise and develop the necessary skillset to work in the smart factory of the future, with a focus on efficiency, productivity, customisation and sustainability.

MAIN ACTIVITIES/RESPONSIBILITIES:
• Conduct a review of existing programmes (including individual modules) being offered at QUB within the Schools of EEECS, Mechanical and Aerospace Engineering, Mathematics and Physics and any other Schools as relevant to the project.
• Provide assistance to the project team in the development of undergraduate programmes in Mechatronics. This includes curriculum development for both classroom and laboratory-based subjects.
• Contribute to the design of a range of academic-related activities on aspects of curriculum development, teaching, learning and assessment, including e-learning that are informed by and consistent with the Higher Education sector and institutional priorities, and are responsive to School needs.
• Closely liaise with the project team and other Schools in QUB to support curriculum development with a cross-disciplinary approach. Developing a close working relationship with relevant industry for requirements capture and for their active involvement in the programme.
• Participate in / contribute, as appropriate, to teaching activity in the subject area.
• Present progress reports to the project team on a regular basis.
• Carry out any other duties designated by the line manager and which fall within the general ambit of the post.

PLANNING AND ORGANISING:
• Plan own day-to day activity within the monitoring, evaluation and dissemination plan of the project.
• Coordinate and liaise with other members of the project team, and consortium (if required) over work progress.

INTERNAL AND EXTERNAL RELATIONSHIPS:
• Regular contact with University staff, both academic and academic support, to facilitate own work activities within the project and to promote a holistic approach to academic support that encourages engagement.
• Represent and promote curriculum development, teaching, learning and assessment, at internal and external meetings to ensure that work/issues are appropriately represented and reported and to contribute to collaborative initiatives.
• Liaise on a regular basis with project partners and industry networks on routine and project-specific matters. Attending regular project meetings with project collaborators as and when needed.
• Develop new and strengthen existing relationships with potential stakeholders, participate in relevant networks for the exchange of information for potential collaboration.

Dr Wasif Naeem

Reader, Energy Power and Intelligent Control Theme

School of Electronics, Electrical Engineering and Computer Science