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Visualization of Knowledge Graphs for Validation, Modification, and Optimization

Applications are invited for a PhD fellowship/scholarship at Graduate School of Science and Technology, Aarhus University, Denmark, within the Computer Science program. The position is available from 1 February 2020 or later.

Visualization of Knowledge Graphs for Validation, Modification, and Optimization

Research area and project description:
Machine learning methods generate models from training datasets. In many cases, these models are obscure and incomprehensible to the human user – who, as a result, remains unsure about what the models encode and whether to trust their predictions. While some uncertainty about their inner functioning may be acceptable when telling dog pictures from cat pictures, in other applications like medicine, autonomous driving, or air traffic control, it is not. For these applications, visualization holds the promise to play an important role in making machine learning results more transparent, traceable, and predictable.

This PhD project sets out to research novel visualization methods for a particular type of machine learning result – so-called Knowledge Graphs. Within an interdisciplinary research project, these graph representations are generated to capture workflows and their relevant context information in hospitals. It will be your task to first and foremost develop visual-interactive techniques to communicate these knowledge graphs to medical experts, so that they can validate and modify these graphs if necessary. Furthermore, you are to explore the possibility of using the resulting visualization as a means for monitoring and optimizing healthcare workflows in hospitals.

Research questions to pursue in this project are:

  • How to show the learned knowledge graph in a way that aligns with the mental map medical doctors have about their hospital’s workflows? In which ways do user preferences and professional background, as well as the task at hand influence this display?
  • What are good starting points for manual modifications of the learned knowledge graph? (e.g., circular or contradicting procedures within the same workflow) How to support manual editing of knowledge graphs by showing its implications in a What-If manner?
  • How to discern between fixed, generally accepted industry-wide procedures and the deviations and more nuanced approaches as employed in a particular hospital, in a particular ward, or only by a particular doctor? How can such a layered approach help to give feedback either to improve the model, or to improve a ward’s or a doctor’s practices?

Work on this PhD topic will be conducted as part of the Hospital@Night project – a grand solution project funded by the Innovationfund Denmark. Within this project, you will collaborate closely with machine learning specialists from the Data-Intensive Systems Group, healthcare IT experts from Systematic, and medical specialists from Aarhus University Hospital und Aalborg University Hospital.

Qualifications and specific competences:
To apply for the position, you must have a relevant Master’s degree and excellent computer programming skills. Prior experience in at least one of the following areas is of advantage: data visualization, data science, computer graphics, human-computer interaction, or database technologies.

You are expected to bring or develop the necessary soft skills for working in teams, as well as for managing and communicating your research progress. The same holds for the necessary hard skills in software development and scientific writing.

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, 8200 Aarhus N, Denmark.

Computer Science started at Aarhus University in 1968 as a part of the Department of Mathematical Sciences. In 1998, computer science became an independent department at Aarhus University (www.cs.au.dk). Today, the department has 125 employees with a great mix of nationalities, and 600 BSc and Msc students on the programs Computer Science and IT product development.

As a PhD student, you are a valuable part of 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. The department host an annual retreat for PhD students and Postdocs, and social events are continuously organized by the Junior Club, which is run by PhD students.

The department is strong in both theoretical and experimental computer science. In recent years, we have seen close cooperation between different research groups – even those that traditionally are perceived as being far from each other. As we emphasize multidisciplinary attitudes to research, no firm dividing lines are drawn between the various strands of subjects, and there is a lively interaction between all research areas. Problem-oriented and inter-disciplinary approaches characterize our research.

Applicants seeking further information are invited to contact:

Assoc. Prof. Hans-Jörg Schulz
Department of Computer Science
University of Aarhus
Åbogade 34
8200 Aarhus N

Office: Hopper-117
E-mail: hjschulz@cs.au.dk
Skype: hajoschulz

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 a Danish 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 September 2019.
Choose November 2019 Call with deadline 1 November 2019 at noon (11.59 AM CET).
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: "Visualization of Knowledge Graphs for Validation, Modification, and Optimization"
  • 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.

All information in the application must be in English or Danish, preferably 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.

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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