Marie Curie ITN Early Stage Researchers in “Data Science and Finance” (2 posts)
Research Project: Distributed and Real-Time Machine Learning for Financial Data Analysis
WP1, Data Science in Finance
This is an opportunity to join the EC Horizon 2020 funded Marie Skłodowska-Curie Innovative Training Network (ITN) “Training for Big Data in Financial Research and Risk Management.
The Early Stage Researcher posts involve a 3-year doctoral programme leading to the award of a PhD from the University of Manchester, and employment as an EU Marie Curie Early Stage Researcher.
BigDataFinance provides doctoral training in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 researchers. The main objectives are i) to meet an increasing commercial demand for well-trained researchers experienced in both Big Data techniques and Finance and ii) to develop and implement new quantitative and econometric methods for empirical finance and risk management with large and complex datasets. To achieve the objectives, the emphasis is put on exploiting big data techniques to manage and use datasets that are too large and complex to process with conventional methods. For more information, please visit: www.bigdatafinance.eu.
For both posts we are looking for bright and motivated individuals with the will to excel in a highly competitive environment. You should have an excellent undergraduate degree (2:1 or above) or MSc ideally in Computer Science or a closely related discipline. You must also be eligible to be appointed as an Early Stage Researcher in the UK.
Please note there are strict *eligibility requirements* which apply to all Marie Skłodowska-Curie Early Stage Researchers. At the time of the appointment, applicants should not hold a PhD or have more than 4 years’ research experience after Undergraduate/Masters graduation and should not have resided in the UK for more than 12 months in the last 3 years immediately before appointment.
The University of Manchester values a diverse workforce and welcomes applications from all sections of the community.
Enquiries about the vacancy, shortlisting and interviews:
Professor John Keane, Professor of Data Engineering
Tel: 0161 306 3334
Dr Xiao-jun Zeng, Senior Lecturer
Tel: 0161 306 3362
Closing date 12/05/2016