Job description and selection criteria

The role

The  senior research scientist, depending on the relevant qualification, is to undertake research in one or more of the following areas:

• Developing science of deep learning based on rough path analysis,
• study risk measures based on rough paths, backward stochastic equations,
• stochastic analysis, stochastic control for rough controlled paths,
• financial modelling and financial data analysis.

These positions are filled as the first phase in the process of establishing a world-class research program in the fundamental research on stochastic analysis and quantitative finance principles to a range of problems arising from natural science and from financial industry, based on the successful theories developed in the past decades by the PIs, in particular on (but not limited to) rough paths and signatures of sequential data. The research scientists will be based at the Oxford-Suzhou Centre for Advanced Research (OSCAR), and will form the core team of the newly established OSCAR Institute for Mathematical Modelling and Data Analytics.  The job will initiate a research program related to establishing the new Institute, launching new research initiatives, maintaining and growing research partnerships with colleagues, engaging and maintaining in collaborative sponsored research with external academic and industrial partners.

In collaboration with his/her academic advisor(s),  Professors T. Lyons, R. Cont, Z. Qian and/or H. Jin, of the Mathematical Institute at the University of Oxford, the post holders will help to lead research programs broadly based in stochastic analysis and quantitative finance and other related research areas, with initial emphasis (but not limited to) on rough path analysis, deep learning via signatures, financial modelling, financial data deep learning, stochastic control, stochastic analysis and etc. The post holders will be founding members of the new Institute and will provide day-to-day running of research activities, serve as a bridge between parallel research efforts based in Oxford and Suzhou, and will interact with partners within the Oxford-Suzhou Centre for Advanced Research.

The successful candidate will possess a doctorate (or be near completion) in a relevant field with experience in one or more of the following areas: stochastic analysis, mathematical finance, statistical mechanics, stochastic control, applied probability, statistics, mathematical physics. Knowledge of stochastic analysis is desirable.

Informal enquiries can be directed to Prof. Z. Qian, email: qianz@maths.ox.ac.uk

Responsibilities

• In collaboration with Prof. Z. Qian, during the initial period,  to have a physical Institute equipped to address problems arising from financial data analysis and the research for large random systems, with specific emphasis on deep learning based on rough path analysis and financial modelling.
• Develop research questions within stochastic analysis, rough path analysis, deep learning based on signatures, stochastic control – classical or via rough paths, financial data simulation and analysis. Conduct theoretical study of rough path analysis, financial models, and risk management by using advanced mathematical tools such as risk measures, backward stochastic equations and stochastic controls.
• Develop and pursue appropriate analytical protocols and techniques to support research.
• Collaborate in the preparation of scientific reports and journal articles. Present papers at national conferences, and lead seminars to disseminate research findings.
• Use scientific computational equipment in a laboratory environment.
• Assist with supervision of research assistants, visitors, where appropriate.
• Contribute to the day-to-day running of the Institute.
• Carry out collaborative projects with colleagues in partner institutions, and research groups.

Selection criteria

Essential

• Hold a relevant Ph.D/D.Phil (or near completion) (with post-qualification research experience for Senior Research Scientist).
• High degree of competence in analytical work.
• Good oral and written communication and presentation skills.
• Possess sufficient specialist knowledge in the discipline to develop research projects and methodologies.
• Strong evidence of research achievement to date, as might be demonstrated by a good publication record and/or academic distinctions and conference prizes.
• The candidate should have experience in one or more of the following areas: stochastic analysis, mathematical finance, statistics, stochastic controls, statistical mechanics, mathematical physics, data analysis, or related subjects.

Desirable

• Expertise in partial differential equations, statistics, and/or machine learning.
• Experience working with financial data, deep learning.
• Demonstrated ability to work in a multidisciplinary team of researchers with a variety of both mathematical and quantitative finance backgrounds.
• Prior experience of instrument interfacing and control and data processing, ideally using Matlab.
• High degree of competence in writing programs involving financial instruments.

About OSCAR (Oxford Suzhou Centre for Advanced Research)  

OSCAR, the first overseas research centre of the University of Oxford, is working closely with the Suzhou Industrial Park and both academic and industrial collaborators in China to progress a range of exciting societal and economic development opportunities.

As a multidisciplinary research, innovation and technology centre, OSCAR focuses on research challenges and technologies that both complement the Centre’s location in Suzhou Industrial Park and capitalise on current Oxford research strengths. Research will initially be focused around the areas of biomedical engineering, biomedicine, advanced functional materials, electronic / optoelectronic / photonic devices, environmental technology, energy, mathematical and computational applications in finance and in health, and other related science and engineering disciplines.

The Centre is positioned in Suzhou Dushu Lake Science and Education Innovation District (SEID), a district in southern SIP with a high concentration of science, education and innovation activity. SEID is the prototype of higher education internationalization in China which hosts 32 local and foreign universities and institutions. The Centre, housed in a nine-storey building with a gross space of 20,000m2, offers flexible access to facilities for multi-functional activities such as labs, seminars, workshops, training, public events, and administration, etc. 

Guidance for Applicants

Thank you for your interest in applying for posts at the Oxford-Suzhou Centre for Advanced Research (OSCAR). Please read the following tips to help you proceed with the application process.

Before the application: 

Please read carefully the job description and selection criteria for the post for which you are applying at the OSCAR website: https://oscar.web.ox.ac.uk to determine whether you have the required skills, knowledge, and experience as advertised. Please DO NOT apply for the posts which are currently unavailable. We typically receive many applications for each post, and so you will need to show in a covering letter how you meet the essential criteria and the desirable criteria in order to be shortlisted for interview.

Required Application documents:

1. Please submit a covering letter and CV (both in English and in PDF) by email attachment to HR@oxford-oscar.cn.
    
2. Email subject: the title of the post for which you are applying. 
    
3. Email content: please include your contact information, name, telephone number, and any dates for which you would not be available for interview.

Covering letter (no longer than one page)

Use the covering letter to explain your motivation for joining OSCAR, and state how your skills and experience match these requirements. Please provide evidence that you have the skills, knowledge, experience, qualifications that match the requirements of the post. The strongest applications provide examples of previous work that demonstrate how you meet the essential and desirable criteria.  Check your spelling and grammar; successful applications are typically proof-read to give the best impression to the selection panel.

Curriculum Vitae (CV, no longer than 8 pages)

Check that your CV is up-to-date and keep your CV within the page limit.  Highlight the skills and experience that are relevant to the post for which you are applying. Avoid sending a generic CV; the strongest applications are those for which CVs are tailored for the needs of the post for which the candidate is applying.  Give details of your education, employment history, publication record, lists of prizes, and voluntary experience.

After the application:

When you submit an application, the information you supply on your application will be provided to a selection panel, who will use it to assess your suitability for the post against the published selection criteria. You may be contacted via e-mail at any date regarding your application.

Your information is held securely in a database that is owned by OSCAR. The data will not be passed to external organisations or individuals other than those acting in a capacity as agents for OSCAR for software support purposes, or where an external body is party to the recruitment process.

When you submit an application to OSCAR you must confirm that you agree to these Terms and Conditions of Use, including the following declaration. 

• The information provided in the application materials is true and complete. I understand that any offer of employment may be conditional upon satisfactory screening. 
• I consent to be contacted by OSCAR at any date regarding my application. 
• I consent to the information given in this application being stored and processed in accordance with the data protection rules at OSCAR. 

Thank you again for your interest in applying for a post at OSCAR.

Recruitment Office

Oxford Suzhou Centre for Advanced Research

Email: HR@oxford-oscar.cn