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Teaching Fellow in Applied Machine Learning

Imperial College London

Location: South Kensington Campus, London

Job Summary

We are a leading department of Electrical and Electronic Engineering in the UK, with a reputation for excellence in both teaching and research. The College obtained a gold rating in the first TEF exercise.

The department is part of the Faculty of Engineering and provides five degree programmes for approximately 850 undergraduate and postgraduate students The post holder will be part of the team responsible for the organization, delivery and innovation in teaching and support.

The primary role of the teaching fellow is to support the student learning experience in machine learning applied in various areas of electrical and electronic engineering. The tasks will mainly include but not be limited to: designing, teaching and assessing topics related to machine learning, deep learning, and engineering of systems that analyse signals from different sensors such as visual, tactile, audio, depth and others.

Deep knowledge of the discipline is essential, as is the ability to use and develop online teaching methods. You will be expected to teach and support lecture modules, coursework and laboratory exercises for undergraduate and postgraduate students and be involved in project design and supervision in the general area of machine learning. You will also be involved in academic and pastoral support duties. As a teaching fellow you need to maintain a high visibility and constant presence in the department for effective student support.

As a teaching fellow you are expected to undertake the full range of teaching, pastoral care and administrative duties in order to improve student engagement and satisfaction in their learning process.

You will be expected to assist with the wider activities in the machine learning laboratories and exercises as specified by the Director of Postgraduate Studies and the Director of Undergraduate Studies. Engagement in pedagogical development classes will be expected for future career progression. The College provides opportunities for training and qualifications, including part-time M.Ed. and Ph.D. courses.

Duties and responsibilities

Teaching / Teaching & Learning Support

  • To design and deliver lectures and tutorials in machine learning, computer science, and robotics for undergraduate and postgraduate students using up-to-date learning and teaching strategies.
  • To meet with student representatives, attend staff-student committee meetings and troubleshoot problems as they arise.
  • To supervise the work of students, provide advice on study skills and help them with learning problems.
  • To set assessments and assess the work and progress of students using appropriate criteria and provide constructive feedback to students, including feedback on reports and course assessments.
  • To participate in the supervision and assessment of student projects and lab experiments.

Learning Technology

  • To design and supervise the production of learning tools in a variety of formats including print, graphics, audio, video and animation technologies to support online lectures, coursework, assessment and feedback.
  • To collaborate with academic staff in the development and implementation of instructional design methods, creating customized web-based instructional elements, and managing online course development with the aim to enhance the impact of online and in-class learning outcomes.

Scholarship

  • To participate in continuing education to maintain an up-to-date knowledge base of new instructional software, of progress in the field of computer engineering and in pedagogical techniques.
  • To present on topics related to blended learning, technology and course design at regional and national meetings.
  • To keep up with the latest development in the field of machine learning.
  • Administration & Other Activities
  • To assist in the admission process for the undergraduate and postgraduate course in applied machine learning.
  • To undertake associated routine administrative tasks that may arise in connection with the above activities.

Essential requirements

Education

  • Educated to minimum M.Sc./M.Eng. level (or equivalent) in a discipline related to Computer Science or Electronic Engineering.

Experience

  • Teaching experience in Computing or Electronic Engineering discipline.
  • Experience in mentoring or dealing with student groups in higher education.
  • Experience in software development.

Knowledge

  • Be proficient in python programming in general and deep learning frameworks in particular and have an ability to teach and inspire students in this area.
  • Be passionate in the area of blended learning methods and problem-based teaching strategies.
  • Theoretical and practical knowledge of classical machine learning and deep learning.
  • Theoretical and practical knowledge of one or more of: Python, Matlab, C++, Java.

Skills & Abilities

  • Be proficient in teaching and engagement of students in higher education.
  • Be able to create an effective module with appropriate assessment methods within the constraints of a project regarding available technology, budget, time and human capital.
  • An ability to be available for student support during working hours.
  • Ability to work autonomously and develop own strategies to respond to deadlines in a timely fashion.

Further Information

To apply, visit www.imperial.ac.uk/jobs and search by the job reference ENG01855.

Further information about the post is available in the job description at the above link.

Should you require any further details on the role please contact Christos Bouganis at christos-savvas.bouganis@imperial.ac.uk.

The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see https://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-evaluation/

The College believes that the use of animals in research is vital to improve human and animal health and welfare. Animals may only be used in research programmes where their use is shown to be necessary for developing new treatments and making medical advances. Imperial is committed to ensuring that, in cases where this research is deemed essential, all animals in the College’s care are treated with full respect, and that all staff involved with this work show due consideration at every level.

https://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-integrity/animal-research

We are committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment for all. We therefore encourage candidates to apply irrespective of age, disability, marriage or civil partnership status, pregnancy or maternity, race, religion and belief, gender identity, sex, or sexual orientation. We are an Athena SWAN Silver Award winner, a Disability Confident Leader and a Stonewall Diversity Champion.

Closing date: 03/10/2021

Location: London
Salary: £45,234 to £53,536 per annum
Hours: Full Time
Contract Type: Permanent
Placed On: 7th September 2021
Closes: 3rd October 2021
Job Ref: ENG01855
 
   
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