Big Data Analytics

- with a focus on Analysis Algorithms, Machine Learning, Visual Analytics and/or their efficient combination to solve Big Data Analysis challenges


Applications are invited for a PhD fellowship/scholarship at Graduate School of Science and Technology, Aarhus University, Denmark, within the Computer Science programme. The position is available from 1 February 2018 or later.


Title:
Big Data Analytics - with a focus on Analysis Algorithms, Machine Learning, Visual Analytics and/or their efficient combination to solve Big Data Analysis challenges.


Research area and project description:
As part of the research project DABAI (www.dabai.dk) funded by the Innovation Fund Denmark, Computer Science at Aarhus University is responsible for several work packages that include PhD projects. The PhD projects should address the following scope and challenges:


DABAI Scope
:
The digitalization of society, industry and businesses has radically transformed work and life throughout the world. Computer Science is a central enabler of this transformation, creating the foundation for new business models and businesses that have grown at unprecedented rates. Today we are experiencing an exponential growth in digital data projected to reach a level of 40 Zettabytes in 2020, up from 2.7 Zettabytes in 2012. It is estimated that with efficient use and analysis of this Big Data, radical new value can be created for society, industry and businesses by, for example, improving process efficiency and predicting disasters, as well as by creating new disruptive businesses. However, many (perhaps most) opportunities in the digitalization and collection of Big Data are not yet being realized. For example, it is estimated that in 2012 only 3% data was tagged with meta data and far less than 3% analyzed. That so little of the available data is being examined points to (i) an underutilization of existing data analysis capabilities in both businesses and government administration, and (ii) a need for new efficient and effective analysis methods and techniques. 

Thus, the DABAI partnership focus on Big Data Analysis research. The focus is supported by the novel integration of research areas needed to develop efficient and
effective solutions, techniques and tools. These include:

1) algorithms for efficient processing of data, 

2) machine learning for data cleaning, analysis, and decision support

3) visual analytics to facilitate exploration and visual interaction with data. 

Combining this integrated research with the development capabilities and a broad solutions portfolio of the core IT-companies and the innovation competencies of the Alexandra Institute, we aim for a novel dual focus on specific domain problems and general tool creation. 

We seek candidates within all three of the above Big Data Analysis disciplines, but we prefer candidates who wish to combine disciplines and approaches to create novel analysis methods.

The PhD students will work in close collaboration with a number of Danish companies and government authorities wishing to stimulate growth and customer value of their Big Data resources. There are a number of different enabling technologies that will be researched and the goal is to develop tools that can support efficient, useful, and valuable data analysis. The DABAI partnership includes more than 5 government entities and 20 companies initially participating in the partnership to tap into the potential of Big Data. Visit www.dabai.dk to get more information, or contact Kaj Grønbæk/Lars Arge as listed below.

Qualifications and specific competences:
Applicants to the PhD position must have a relevant Master’s degree and experience within one or more of the research themes is an advantage.

Place of Employment and Place of Work:
The place of employment is Aarhus University, and the place of work is Department of Computer Science,  Åbogade 34, DK-8200 Aarhus N, Denmark. 

Contacts:
Applicants seeking further information are invited to contact:

Kaj Grønbæk, Professor, PhD,
Department of Computer Science, University of Aarhus,
Aabogade 34, DK-8200 Aarhus N, Denmark.
E-mail: kgronbak@cs.au.dk
Cell phone: (+45) 2149 5634

OR

Lars Arge, Professor, PhD,
Department of Computer Science, University of Aarhus,
Aabogade 34, DK-8200 Aarhus N, Denmark.
Email: large@cs.au.dk
Cell ph: (+45) 4160 6166


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 Graduates School of Science and Technology is comparable to an “English B level” in the Danish upper secondary school (“gymnasium”).

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

  • TOEFL test, minimum score: 560 (paper-based test) or 83 (internet-based test). Aarhus University does not accept the TOEFL ITP test. Aarhus University’s TOEFL code is 8935. You must request that the test centre 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, United Kingdom, 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, United Kingdom, or 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”.
  • Applicants able to document that English was the language of instruction during the whole period of their Bachelor’s and/or Master’s programme. This must be documented by uploading an official document from the institution stating this under “language skills documentation”. The onus is on the applicant to provide this information as GSST will not pursue information regarding language of instruction for any programmes or institutions.

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 http://talent.au.dk/phd/scienceandtechnology/opencalls/
Choose November 2017 Call with deadline 1 November 2017 at 11.59 PM MET.
You will be directed to the call, and must choose the programme 'Computer Science'

2)      Fill in the following information:

  • Personal information
  • Academic background
  • Admission
  • Financing (if any)
  • Study: In the dropdown menu you must choose the project: "Big Data Analytics"
  • 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 and diploma(s)
  • Project description (½-4 pages). For technical reasons, you must upload a project description. When - as here - you apply for a specific project, please simply copy the project description above, and upload it as a PDF in the application. Since the call is covering several different themes within Data Analysis, the applicant need to indicate which themes the find of interest.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. In case of 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 here.

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.