The Department of Applied Mathematics and Theoretical Physics invites applications for a Senior Teaching Associate and Industrial Training Co-ordinator in the field of Data Intensive Science. This position would be directly connected to both the new MPhil in Data Intensive Science and an associated Industrial Training Programme based on the core material.
The MPhil is supported by the Department of Applied Mathematics and Theoretical Physics, the Institute of Astronomy, and the Department of Physics and has been designed in collaboration with our leading researchers and industrial partners to provide students with expert training in Machine Learning (ML), Statistics, Computing, and their application to research. The MPhil will initially welcome a cohort of 50 students, but this is expected to grow to 100 over 5 years.
An Industrial partner has asked that the core material be adapted to form a comprehensive employee training in Machine Learning and AI. This will take the form of recorded lecture materials with supporting example sets and supervision support. The programme will initially train 30 expert trainers in the partner organisation who will then support the programme being rolled out within the company.
The successful candidate will have extensive experience analysing scientific data sets, either in academia or industry, preferably in one of the research areas mentioned above. They should have a proven track record of teaching and be an excellent communicator. They should be able to demonstrate a comprehensive understanding of, and show practical experience with, statistical methods and machine learning algorithms. They must be highly organised and motivated and should demonstrate aptitude for programme coordination. They must also be proficient in Python and the techniques required for software development best practice. Familiarity with other coding languages, in particular C++, and high-performance computing is desirable. It is expected that they will hold a PhD in mathematics or physics (or a cognate discipline).
The successful candidate will be expected to support the MPhil by: the creation and delivery of course modules; the supervision, assessment, and examination of modules; and the provision of computational projects for the new Master's degree. They will support the Industry Training programme by coordinating the training material and overseeing its delivery by our teaching team. This will primarily involve ensuring the content is clearly presented, coherent across topics and lecturers, appropriate to the trainee's level, is delivered in a timely manner and is of a high standard. They will also be expected to participate in the administration of tasks associated with the academic delivery of these two programmes.
Due to the fast-moving nature of the topics covered in the programmes, the role holder would be expected to participate in one or more of the research groups in the department to maintain their knowledge of the current status of research and techniques used within them.
A new Academic Career pathway scheme for Teaching and Scholarship staff has been developed to recognise and reward outstanding contributions and celebrate academic achievement through promotion and/or pay progression. This post falls within this career pathway scheme. Further details are available here www.acptands.hr.admin.cam.ac.uk.
The Departments are active in promoting policies to address historic under-representation of women and minority groups in its workforce. Candidates from under-represented groups, as well as candidates with a track record in addressing barriers to equality and diversity in education, are particularly encouraged to apply.
Fixed-term: The funds for this post are available for 3 years in the first instance.
Informal enquiries regarding the application process can be sent to the Mathematics HR Office, email: LE34338@maths.cam.ac.uk.
For informal enquiries please contact Assoc. Prof. James Fergusson (Email: firstname.lastname@example.org).
Please upload a full curriculum vitae and an experience statement of up to two pages setting out your past work in Data Intensive Science and how it relates to the skills required for this position. This should include a description as to how it connects with existing research activities associated with the programmes.
Please also upload a teaching statement of up to two pages setting out your approach to teaching and the contributions you can make to the new MPhil programme in Data Intensive Science.
Please indicate the contact details of three professional referees on the online application form and ensure that at least one of your referees is contactable at any time during the selection process, and is made aware that they will be contacted by the Mathematics HR Office Administrator to request that they upload a reference for you to our Web Recruitment System; and please encourage them to do so promptly.
Please quote reference LE34338 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
|Salary:||£38,592 to £51,805|
|Placed On:||5th December 2022|
|Closes:||8th January 2023|
Type / Role:
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