PhD Studentship - Financial Data Science 

Goldsmiths University of London
February 24, 2023
Contact:N/A
Offerd Salary:£18,000
Location:N/A
Working address:N/A
Contract Type:Other
Working Time:Full time
Working type:N/A
Ref info:N/A
PhD Studentship - Financial Data Science

Department

Computing

Vacancy Type

Studentship

Full-Time/Part-Time

Full Time

Salary

More information below

Actual Hours

35

FTE

TBC

Interview Date

TBC

Contact Details

r.venkatachalam@gold.ac.uk or l.soldatova@gold.ac.uk

Posted Date

16/01/2023

Closing Date

24/02/2023

Ref No

9834

Documents

  • Full Job Description (PDF, 174.02kb)
  • PhD Studentship – Financial Data Science

    Goldsmiths

    Goldsmiths University of London is a world-leading centre of educational excellence where ground-breaking research meets innovative teaching and thinking. We are looking for inspiring, talented people to help Goldsmiths build on its global reputation as we expand our capabilities as a learning organisation.

    As a college we are working to tackle inequality in all its forms and are working to promote equality on grounds of race, disability, age, sex, gender identity, sexual orientation, religion and belief, marriage and civil partnership, pregnancy and maternity, and caring responsibilities. We are keen to attract candidates from diverse backgrounds who share our commitment to creating an inclusive culture in which all students and staff can thrive.

    Introduction / The role

    The Department of Computing at Goldsmiths, University of London, has a vacancy for a PhD student position in the area of data science in finance. The position will be co-supervised by both Dr.Venkata L. Raju Chinthalapati and Prof. Larisa Soldatova.

    The PhD project will involve bringing a scientific approach into economics/finance research using cutting-edge methods and technologies. For example, can we point out things that are not normal in a market that may look normal? Most believe the answer lies in big data analytics. Digitalization of finance brings rich data sets and mining the big data that enters the markets around the world each day identifies the key insights.

    The latest advancements in analytics, big data technologies and research in financial economics provide us with the opportunity to gain game-changing insights. The outcomes of this research related to big data in finance help us in understanding market microstructure, information asymmetry, liquidity risk and stability of financial markets. In addition to that, this research democratises the investment analytics that helps 1) automating portfolio management and 2) creating robo-advisors.

    Eligibility

    Applicants should have a master's degree in Computer Science, Mathematics, Economics, Finance or a related discipline. Candidates should have excellent communication (oral and written) and programming skills (one or more of the programming languages Python,Java,C/C++).

    Applicants who also demonstrate deep knowledge of time-series analysis, machine learning and familiarity of big data technologies will be favoured.

    Knowledge of financial data analysis is not a must, but applicants should be interested in financial data analysis.

    Funding

    The studentship is for 3 years and provides full coverage of tuition fees (Home and Overseas) and an annual tax-free stipend of £18,000. The funding is provided by Goldsmiths. University of London.

    To Apply

    You are strongly encouraged to discuss your application in advance with Dr. Venkata L. Raju Chinthalapati (Email: V.Chinthalapati (@gold.ac.uk) and Prof. Larisa Soldatova.

    (Email: l.soldatova (@gold.ac.uk)

    Please submit your application by clicking the Apply button, including the following documents:

  • A CV that includes information about education background and work/research experience

  • Certified copies of relevant transcripts and diplomas.

  • A short research statement explaining the experience and the interest of the candidate for the research topic and describing the relevance of the candidate's background to the research project (max 1 page)

  • A copy of the master thesis.

  • Any relevant publications.

  • Contact information for two references.

  • Application Deadline is Friday 24 February 2023. Proposed start date is negotiable.

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