Research Assistant / Associate
Causal discovery techniques provide means for identifying cause-effect relations in a given dataset; a task which common machine learning methods fail to do (adequately). However, in many application areas that involve human-decision making, such data are not always available, or maybe inconsistent, thus hindering the applicability of such methods. Symbolic learning techniques have the advantage of being able to learn general rules from small,...
Job listing information
- Reference ENG01989
- Date posted 22 December 2021
- Closing date 16 January 2022
Causal discovery techniques provide means for identifying cause-effect relations in a given dataset; a task which common machine learning methods fail to do (adequately). However, in many application areas that involve human-decision making, such data are not always available, or maybe inconsistent, thus hindering the applicability of such methods. Symbolic learning techniques have the advantage of being able to learn general rules from small, noisy datasets and (human) domain knowledge. In this project, we are interested in improving symbolic learning methods so that they can learn context-dependent, causal rules to aid human decision-making.
We are seeking a highly motivated applicant for a Research Assistant/Associate post to play a critical role to this end. This project is being conducted by a consortium of universities (University of Birmingham, University of Leicester and Imperial College London). The research contract is initially agreed for four months starting asap but follow-on funding is anticipated (although cannot be guaranteed).
The Department of Computing at Imperial College London is a leading department of Computer Science among UK Universities. The department has achieved top results in each of the research assessment exercises undertaken by the Higher Education Funding Council for England. There are over fifty academic staff members actively involved in research, creating a lively and stimulating atmosphere. The department is located in central London, next to Hyde Park and the museums of South Kensington.
Duties and responsibilities
The project is part of an ongoing collaboration with the National Crime Agency (NCA) aimed at developing decision-support for the crime linkage of serial sex offences (the practice of linking offences suspected to be committed by the same individual).
The successful applicant will have a strong background in symbolic reasoning and/or machine learning research, and will be comfortable working across disciplines. She/he will be expected to develop research initiatives within the scope of the position, design and implement novel analysis techniques, conduct experiments, and assist in developing further projects with partners.
The project is an exciting opportunity for the post holder to build theoretical and practical experience in the design of hybrid machine learning systems with societal impact. The post-holder will be part of a multidisciplinary team investigating algorithmic support for linking serial sexual offences, and will thus have the opportunity to develop her/his expertise on dissemination of research through interactions with other researchers in forensic psychology and criminology, and with end-users.
Applicants should have completed or soon expect to complete a PhD in computer science or related discipline, and one or more high-quality publication(s) in relevant venues. Candidates must be prepared to sign the Official Secrets Act and information sharing agreements, and may require travel to NCA sites at times.
Please see job description for full list of requirements
*Candidates close to completion of their PhD will be initially appointed as a Research Assistant within the salary range £36,694 - £39,888 per annum, pro rata.
In addition to completing the online application candidate should attach.
- A two-page CV including a publication list.
- A two-page research statement
Informal inquiries are encouraged and can be addressed to Dr Dalal Alrajeh: firstname.lastname@example.org
For queries regarding the application process contact Jamie Perrins: email@example.com
About Imperial College London
Imperial College London is the UK’s only university focussed entirely on science, engineering, medicine and business and we are consistently rated in the top 10 universities in the world.
You will find our main London campus in South Kensington, with our hospital campuses located nearby in West and North London. We also have Silwood Park in Berkshire and state-of-the-art facilities in development at our major new campus in White City.
We work in a multidisciplinary and diverse community for education, research, translation and commercialisation, harnessing science and innovation to tackle the big global challenges our complex world faces.
It’s our mission to achieve enduring excellence in all that we do for the benefit of society – and we are looking for the most talented people to help us get there.
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.
Imperial College is committed to equality of opportunity and to eliminating discrimination. All employees are expected to follow the Imperial Values & Behaviours framework. Our values are:
In addition to the above, employees are required to observe and comply with all College policies and regulations.
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.
For technical issues when applying online please email firstname.lastname@example.org.
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