Marie-Curie Early Stage Researcher in financial data analysis  - Nikhef / KPMG

We invite applications for the post of Marie-Curie Early-Stage Researcher (ESR) at Nikhef, Amsterdam as part of INSIGHTS (International Training Network for Statistics in High Energy Physics and Society).  INSIGHTS is an EU-supported "Marie Curie Action" project, which funds PhD students in an interdisciplinary programme that includes specialised schools, workshops and secondments in industries and research centres. The ESR candidate will be enrolled in the PhD programme in the the university of Amsterdam and carry out a thesis in High Energy Physics with the ATLAS Collaboration at the Large Hadron Collider (LHC) at CERN.  The candidate must not have been resident in the Netherlands for more than 12 months in the 3 years prior to the start date (further eligibility criteria are given below).
About INSIGHTS
The INSIGHTS network is focused on the development and application of statistical methods for elementary particle physics, as carried out, for example, at research facilities such as the Large Hadron Collider at CERN, near Geneva.The supported researchers will develop and apply research tools for physics from fields such as machine learning, software engineering, parametric modelling and Bayesian computation.  An important component of the network involves knowledge exchange with areas outside particle physics, including finance, risk modelling, volcanology, and climate science. 
The INSIGHTS Consortium consists of partners from the UK the United Kingdom (Royal Holloway University of London, University of Edinburgh), Italy (PANGEA, University of Naples, INFN), the Netherlands (Nikhef), Germany (Max-Plank Institute), Switzerland (CERN), Sweden (Lund University) and Norway (University of Oslo). 

Project and job description

Since the financial crisis in 2008 strict regulatory requirements on data quality have been introduced by the European and national banks for the financial sector. While 100% data quality is the imposed target level, it is recognized that this is an unrealistic number from a practical perspective. Missing from a data analytics perspective, are scientific tools that treat residual data failures and mistakes as systematic uncertainties, and that propagate these systematic effects in the predictions coming from financial risk models. In other words tools that are able to quantify the accuracy and reliability of the predictions of models and algorithms under the assumption that the data is not 100% correct.

The PhD candidate will develop a simulation framework that allows simulation of (historic) data and systematic effects to test the robustness and reliability of algorithms and models. The framework should be able to autonomously identify and extract relevant correlations from any given dataset and simulate a dataset that reproduces these correlations. Furthermore, the framework should be able to generate distortions to these (simulated) datasets that reflect in various levels the impact of known and measured data quality issues. The distorted datasets are fed into risk models to study the robustness of an algorithm or model and to assess the impact of (systematic) uncertainties on financial risk models. It should also be possible to simulate alternative scenarios, i.e. (business) policies or decisions, within this framework. The goal being to identify the optimal scenario according to an arbitrary set of criteria from e.g. an economical or societal point of view.

Requirements

Candidates should have completed a master in computer science or a related field, or will do so on short term. On a masters level, the candidates must have knowledge of statistics, model building, mathematics and strong coding abilities. Knowledge of ABM-based simulations is considered as a pre. The candidates must have the ability to give demonstrations to scientific and business audiences. Their grades demonstrate their knowledge and ambition, their master thesis their ability to continue with a PhD research in Computer Science. Marie Sklodowska-Curie eligibility rules require Early-Stage Researchers to have at most four years' research experience, counting from the date at which they have been awarded a degree that allows them to embark on a PhD. To satisfy Marie Sklodowska-Curie mobility criteria, you must not have resided or carried out your main activity (work, studies, etc.) in the Netherlands for more than     12 months in the 3 years immediately prior to the start date (short stays such as holidays and/or compulsory national service are not taken into account). The Marie Sklodowska-Curie programme places no restrictions on nationality: applicants can be of any nationality and currently resident in any country worldwide, provided they meet the eligibility requirements set out above.
Appointment
Appointment
The appointment will be full-time (38 hours a week) for a period of four years. The initial employment period of 18 months is funded through Nikhefs participation in the INSIGHTS Marie Sklodowska-Curie programme. Periodic evaluations will be held after 9 and 14 months, and upon positive evaluation, the appointment will be extended at the Informatic institute of the University of Amsterdam to a total of 48 months  The appointment must lead to a dissertation (PhD thesis). An educational plan that includes attendance of courses, summer and/or winter schools, and national and international meetings will be drafted for the PhD candidate. We also expect the PhD candidate to assist in teaching of undergraduate students. Among other things, we offer:
  • competitive pay and good benefits;
  • top-50 University worldwide;
  • one of the best deep learning ecosystems in the world;
  • interactive, open-minded and a very international city;
  • excellent computing facilities.
English is the working language in the Informatics Institute. As in Amsterdam almost everybody speaks and understands English, candidates need not be afraid of the language barrier.
The selection process commences immediately and continues until a suitable candidate is found.. We will accept applications until 12 June 2018 (extended as long as no suitable applications have been received)
Further information on this position can be obtained from prof. dr. Sander Klousi (s.klous@uva.nl) or prof. dr. Tom M van Engers (vanengers@uva.nl)


Apply now
 

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