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Data-driven Inter-Stock Predictive Analytics (DISPA)

Applications are invited for a PhD fellowship/scholarship at Graduate School of Science and Technology, Aarhus University, Denmark, within the Engineering programme. The position is available from 1 November 2019 or later.

Title:
Data-driven Inter-Stock Predictive Analytics (DISPA)

Research area and project description:
The project is supported by a grant by the Independent Research Fund of Denmark for conducting basic research in machine learning-based financial econometrics. Work will be focused on proposing new techniques and methodologies for financial time-series analysis, data summarization and visualization based on state-of-the-art deep learning approaches. The popularized description of the project is as follows:

The identification of fraud trading activities and illegal manipulations of stock markets requires years of intensive work by experts, and a certain level of luck since investigations are not conducted systematically for all cases. There is a significant potential for machine learning solutions to make the systematic analysis possible by greatly reducing manual effort and the associated costs through identifying irregular activities and determine inter-stock interactions. This project, under the hypothesis that trades in a stock affecting the status of other stocks and their future trades can be determined using data-driven analysis, will design novel methods for inter-stock fraud activity detection and prediction. We focus on trading activity summarization based on the identification of jumps in the mid-price of stocks. We will detect similarly behaving stocks based on real trading activity to reveal relations between stocks and indirect irregular trading actions.

Supervisor will be Associate Professor Alexandros Iosifidis. For more information about his work, see http://pure.au.dk/portal/da/ai@eng.au.dk and https://sites.google.com/view/iosifidis.

Qualifications and specific competences:
Applicants to the PhD position must have a Master’s degree in Computer Science, Informatics, Electrical & Computer Engineering, or equivalent. Competence in programming, mathematics, and relevant topics in pattern recognition and machine learning are an advantage. The applicant should be enthusiastic about working in an interdisciplinary academic environment.

Place of employment and place of work:
Department of Engineering, Aarhus University, Finlandsgade 22, 8200 Aarhus N, Denmark.

You will be a member of the Data-Driven Analytics group, which is strong in both theoretical and applied aspects of machine learning and its sub-areas (like deep learning and kernel methods). In recent years, we have seen close cooperation between different research groups around the world.

As a PhD student, you are a valuable part of the group and the department. All PhD students get a support group of experienced advisors outside their own research group. The main purpose of the support group is to give feedback on the PhD work to help you reach your full potential as PhD student, and to ensure that any obstacles that may arise are overcome as smoothly as possible. Another important aspect is socializing with your peers across the department. Social events are continuously organized by the department and student clubs.

Aarhus University was founded in 1928. It has 40,000 students; about 1,800 PhD students – of which one in four has a foreign nationality – and close to 900 postdoctoral scholars together with 11,500 employees. Aarhus University has been establishing itself as a university for cutting-edge research, and has been regularly included in the top-100 Universities of the most important university ranking lists.

Contacts:
Applicants seeking further information are invited to contact:

Associate Professor Alexandros Iosifidis (ai@eng.au.dk)

 

Application procedures

Before you apply

Information and attachments:

Please be aware that you must have all relevant appendices, attachments, addresses for referees, etc. ready when you apply, as the entire application must be uploaded to the system in one go.

Documentation of language skills:

The English language requirement at GSST is comparable to an “English B level” in the Danish upper secondary school (“gymnasium”).

English language qualifications comparable to an “English B level” are documented by one of the following tests:

  • TOEFL test, minimum score: 560 (paper-based test) or 83 (internet-based test). The paper-based test must have a “total score”. From the August 2019 call, GSST will no longer accept the paper-based test.
    Aarhus University does not accept the TOEFL ITP test. Aarhus University’s TOEFL code is 8935. Ask the test centre to send your test results to Aarhus University, in order to enable verification of your test results.
  • IELTS (academic) test, minimum average score: 6.5 points
  • Cambridge English Language Assessment:
    Cambridge Certificate of Proficiency (CPE)
    Cambridge English: Certificate of Advanced English with grade A,B or C (CAE)
    Cambridge English: First Certificate  with grade A (FCE)

When to take the test and how to upload the documentation:
The test result must not be more than two years old at the time of application.

The English language test should be taken before applying for admission and uploaded under “language skills documentation” in the online application form.

It is possible to apply for admission before you have taken the test. In this case documentation stating that you have signed up for a test (please state expected submission date) must be uploaded. If the test result is not part of the original application the test result is to be sent to sphd@psys.au.dk no later than one month after the application deadline.

The following applicants are exempted from documenting their English qualifications/taking a test:

  • Applicants with citizenship from the following countries: Australia, Canada, Ireland, New Zealand, the United Kingdom, the United States, or one of the Nordic countries (Denmark, Finland, Iceland, Norway or Sweden).
  • Applicants with a Bachelor’s or Master’s programme completed in Australia, Canada, Ireland, New Zealand, the United Kingdom, or the United States. In this case, please upload your Bachelor’s or Master’s diploma under the section ”Language skills documentation”.
  • Applicants with a Bachelor’s or Master’s programme completed at Aarhus University for which the requirement was English B level at the time of admission. In this case, please upload your Bachelor’s or Master’s diploma under the section” Language skills documentation”.

The programme committee may request further information or invite the applicant to attend an interview.

How to apply:

1)      Find the application form:
Go to www.phd.scitech.au.dk/for-applicants/apply-here - Note, the online application system opens on 1 June 2019.
Choose August 2019 Call with deadline 1 August 2019 at noon (11.59 AM MET).
You will be directed to the call, and must choose the programme 'Engineering'

2)      Fill in the following information:

  • Personal information
  • Academic background
  • Admission
  • Financing (if any)
  • Study: In the dropdown menu you must choose the project: "Data-driven Inter-Stock Predictive Analytics (DISPA)"
  • Source (how you found out about the call)

Next to some of the information fields you will find a number. Click on the number to get further directions on how to fill in the information field/what information is needed.

3)      Application attachments:
Please be aware that you cannot submit the application if one or several of these documents have not been uploaded.

If you wish to upload more than one document under each section, you must scan/merge all documents into one large PDF file and upload this. Please note that we reserve the right to remove scientific papers, large reports, theses and the like. Instead you can indicate a URL where the information is available.

Please note that all information in the application must be in Danish or English.

As a minimum all applications must include (pdf-files only, max. 20 MB, no zip):

  • One reference (template for references)
  • Curriculum vitae,
  • Motivation (max. 1 page)
  • Transcripts, grade point averages (weighted and unweighted), and diploma(s) for both Bachelor’s and Master’s degree
  • Project description (½-4 pages). This document should describe your ideas and research plans for this specific project. If you wish to, you can indicate an URL where further information can be found. Please note that we reserve the right to remove scientific papers, large reports, theses and the like.
  • Documentation of language skills if required.

After submission of the application, you will receive a confirmation e-mail with an application ID, you should use for reference if needed. The e-mail will also include a link to the application – GSST urges you to check that all mandatory data, marked with an asterisk (*), is registered correctly and all attached files are readable. If there are any significant errors, you should reply to the confirmation e-mail with the correct details before the application deadline.

GSST reserves the right to verify the authenticity of your educational diploma and transcripts:

  • Request additional information to verify an application.
  • Reject the application if it is proven, or if the University has reasonable belief, that the information provided is false or if the applicant refuses to provide the requested information, whether or not an offer has already been made. 
  • For further information on applying, assessment procedures, etc. please see the GSST Application Guide.  

Please note:

  • The programme committee may request further information or invite the applicant to attend an interview.

All interested candidates are encouraged to apply, regardless of their personal background.



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