Research Associate in Machine Learning

Job summary

Applications are invited for the position of Research Associate to be held jointly with the Department of Computing and the Department of Mathematics. The research associate will work on the theoretical foundations of stable machine learning algorithms, and deep neural networks in particular. The research associate will work on the theoretical foundations of stable machine learning algorithms, and deep neural networks in particular. ...

Job listing information

  • Reference ENG00790
  • Date posted 1 April 2019
  • Closing date 30 April 2019

Job description

Job summary

Applications are invited for the position of Research Associate to be held jointly with the Department of Computing and the Department of Mathematics. The research associate will work on the theoretical foundations of stable machine learning algorithms, and deep neural networks in particular. The research associate will work on the theoretical foundations of stable machine learning algorithms, and deep neural networks in particular. 

Breakthroughs in modern Neural Network (NN) architectures and related algorithms in Machine Learning (ML) have entirely transformed whole areas of computer science such as computer vision and natural language processing. Recent research papers, propose to use deep neural networks to solve otherwise intractable problems in finance such as pricing and hedging in high dimensions and to model price formation using high-frequency data. Unfortunately, both theoretical and empirical results have shown that neural networks compute unstable classifiers. An unstable classifier is vulnerable to adversarial attacks and illegal exploitation. A necessary condition for successful ML systems in real-world applications, especially ones in the financial sector, is that the underlying system is stable. Without resolving this challenging problem, it is not possible to make meaningful progress in critical application areas such as the explainability and interpretability of machine learning algorithms, or efficient and robust training methods for reinforcement learning.

Duties and responsibilities

The Research Associate will work directly with Dr. P. Parpas, Dr. N. Kantas, Professor G.A. Pavliotis at Imperial College and the AI research Team in JP Morgan. They will join a large, vibrant research team working on problems related to machine learning, optimization, stochastic optimal control, partial differential equations, quantitative finance, statistical mechanics and stochastic differential equations.

Essential requirements


  • A PhD (or equivalent) in Mathematics, Statistics, Computer Science, Engineering, Physics, or a related area, or an equivalent level of professional qualifications.

  • Excellent record of accomplishment in carrying out original research of high quality in at least two of the following areas: optimization, machine learning, dynamical systems, optimal control, numerical analysis, or stochastic processes.

  • Strong programming skills.

  • Excellent oral and written communication skills.

  • Able to organise your work with minimal supervision and prioritise work to meet deadlines.

Further information

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £33,397 - £37,486 per annum.

In addition to completing the online application, candidates should attach:

  • A full CV
  • A two-page research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.

Should you have any queries regarding the application process please contact Jamie Perrins: j.perrins@imperial.ac.uk

For technical issues when applying online please email recruitment@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. http://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-integrity/animal-research

 

Documents

About Imperial College London

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Additional information

Please note that job descriptions cannot be exhaustive and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.

All Imperial employees are expected to follow the 7 principles of Imperial Expectations: 

  • Champion a positive approach to change and opportunity
  • Communicate regularly and effectively within, and across, teams
  • Consider the thoughts and expectations of others
  • Deliver positive outcomes
  • Encourage inclusive participation and eliminate discrimination
  • Develop and grow skills and expertise
  • Work in a planned and managed way 

In addition to the above, employees are required to observe and comply with all College policies and regulations.

Imperial College is committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment. We are an Athena SWAN Silver award winner, a Stonewall Diversity Champion, a Disability Confident Employer and work in partnership with GIRES to promote respect for trans people.