Visit All-Acad.com with more than 200,000 Jobs for Academics!
                    
Position: Research Associate - Statistics
Institution: Imperial College London
Department: Mathematics
Location: London, United Kingdom
Duties: Applications are invited for a Research Associate position to work in the area of Bayesian Non-Parametric statistics. The advertised position is based in the vibrant Statistics section of the Department of Mathematics, and is to work in collaboration with researchers in the School of Public Health and at the MRC-PHE Centre for Environment and Health
Requirements: The successful candidate must hold a PhD (or equivalent) level of professional qualifications in statistics, mathematics, computer science or closely related discipline. A desire to develop statistical methodology for conditional independence testing in a Bayesian Non-Parametric framework. Experience in carrying out research of high quality, independently and/or in a team, evidenced by publications of high quality. A strong background in statistics
   
Text: Research Associate in Statistics Apply now Save this job Job summary Applications are invited for a Research Associate position in the Department of Mathematics at Imperial College London to work in the area of Bayesian Non-Parametric statistics. The position is funded through the EPSRC Grant EP/R013519/1. The Research Associate will work directly with Dr Sarah Filippi who holds a joint position between the Department of Mathematics and the School of Public Health. The advertised position is based in the... Job listing information Reference NAT00152 Date posted 20 April 2018 Closing date 25 May 2018 Key information about the role Location South Kensington Campus (map) Position type Full time, fixed term Salary £36,800 - £44,220 plus benefits Department Department of Mathematics Category Researcher / Non Clinical Researcher Job description Job summary Applications are invited for a Research Associate position in the Department of Mathematics at Imperial College London to work in the area of Bayesian Non-Parametric statistics. The position is funded through the EPSRC Grant EP/R013519/1. The Research Associate will work directly with Dr Sarah Filippi who holds a joint position between the Department of Mathematics and the School of Public Health. The advertised position is based in the vibrant Statistics section of the Department of Mathematics, and is to work in collaboration with researchers in the School of Public Health and at the MRC-PHE Centre for Environment and Health. Duties and responsibilities The post holder will work on developing a novel Bayesian Non-Parametric Test for Conditional Independence. This is at the core of modern causal discovery, itself of paramount importance throughout the sciences and in Machine Learning. As part of this project, the post holder will derive a Bayesian non-parametric testing procedure for conditional independence, scalable to high-dimensional conditioning variable. To ensure maximum impact and allow experimenters in different fields to easily apply this new methodology, the post holder will then create an open-source software package available on the R statistical programming platform. Doing so, the post holder will investigate applying this approach to real-world data from our established partners who have a track record of informing national and international bodies such as Public Health England and the World Health Organisation. This should position the post holder ideally for the next steps in their career, by furthering their track record of bridging theory and applications in concrete ways. Essential requirements This should position the post holder ideally for the next steps in their career, by furthering their track record of bridging theory and applications in concrete ways. It is essential that you have: • The successful candidate must hold a PhD (or equivalent) level of professional qualifications in statistics, mathematics, computer science or closely related discipline. Experience and knowledge: • Desire to develop statistical methodology for conditional independence testing in a Bayesian Non-Parametric framework. • Experience in carrying out research of high quality, independently and/or in a team, evidenced by publications of high quality. • A strong background in statistics . Skills and abilities: • Ability to work and communicate effectively in a multi-disciplinary team. • Ability to carry out original research and publish in high impact journals. • Ability to exercise initiative and judgment in carrying out research tasks. • Ability to prioritise own work in response to deadlines. • Ability to identify, develop and apply new concepts, techniques and methods. • Creative approach to problem-solving. • Ability to organise and prioritise own work with minimal supervision. • Ability to keep accurate records of research results and activity. • Excellent written communication skills and the ability to write scientifically, clearly and succinctly for publication. • Ability to present research with authority and coherence. Further information Please complete and upload an application form as directed, also providing a CV and a list of publications. For any specific queries regarding the post please contact Dr Sarah Filippi s.filippi@imperial.ac.uk) Should you have any queries about the application process please contact Ms Mona El-Khatib, (m.el-khatib@imperial.ac.uk). For technical issues when applying online please email recruitment@imperial.ac.uk * Maximum salary on appointment £36,800. Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £32,380 - £34,040 per annum. 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. 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.
Please click here, if the Job didn't load correctly.







Please wait. You are being redirected to the Job in 3 seconds.