Doctoral student in Explainable and Probabilistic Deep Learning - Hiring in process/Finished, not possible to apply

Project description

Third-cycle subject: Computer Science

There is a crucial need for trust in real-world applications of AI. Two main aspects that enable trust in an AI model are 1) human-explainability of AI’s predictions and 2) the AI’s understanding of its own uncertainty in making those predictions. The scientific work of this doctoral project will focus on developing modern explainable and probabilistic deep learning methods to perform general recognition tasks with a special focus on visual data. The explainability comes by design in this project as opposed to the post-hoc methods. The probabilistic approach will be based on the recent developments in probabilistic deep discriminative and generative networks. The project will benefit from collaborations with other group members focused on either of this project’s aspects (list of publications).

The role of the doctoral student will be to focus on developing theoretical advances and applying them to general computer vision benchmarks or real-world life science applications. Should the student be willing and experienced enough, they will have freedom to steer the direction of research. 

Supervision: The doctoral student will be supervised by: Assistant Professor Hossein Azizpour

What we offer

• The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from all over the world. Read more
• A postgraduate education at an institution that is active and supportive in matters pertaining to working conditions, gender equality and diversity as well as study environment.
• A workplace with many employee benefits and monthly salary according to KTH’s doctoral student salary agreement.
• Access to a vibrant group with several related academic activities including reading groups, international seminar series, and joint group meetings.
• Access to real-world multi-disciplinary projects including life science, monitoring and modeling urban pollutants and urbanization, and monitoring and modeling forest fires.
• Access to state-of-the-art GPU resources for deep learning research
• Financial support for the presentation of own’s and collaborative works at international venues.

Eligibility

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility per either of the following:

• passed a degree at an advanced level,
• completed course requirements of at least 240 higher education credits, of which at least 60 higher education credits at an advanced level, or
• in any other way acquired within or outside the country acquired essentially equivalent knowledge.
• Requirements for English equivalent to English B/6, read more here.

Selection

During the selection process, candidates will be assessed by the following criteria.

• Mathematical background especially in probabilistic modeling.
• Experience and education in both theory and practice of machine learning, especially deep learning.
• Good command of English, strong motivation for doctoral studies, independence, critical analysis, cooperative and communication skills. 
• Prior experience with remote GPU and HPC services.

After the qualification requirements, great emphasis will be placed on personal competency. 

Target degree: Doctoral degree

Information regarding admission and employment

Only those admitted to postgraduate education may be employed as doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education of four years. To a limited extent (maximum 20%), an employed doctoral student can perform certain tasks within their role, e.g. teaching and administration. A new position as a doctoral student is for a maximum of one year, and the employment may be renewed for a maximum of two years at a time.

Union representatives

You will find contact information for union representatives on KTH's website.

Doctoral section (Students’ union on KTH Royal Institute of Technology)

You will find contact information for the doctoral section on the section's website.

Application

Apply for the position and admission through KTH's recruitment system. It is the applicant’s responsibility to ensure that the application is complete per the instructions in the advertisement.

Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/Central European Summer Time).

Elements:

• CV including your relevant professional experience and knowledge.
• A brief account of why you want to pursue research studies, about what your academic interests are, and how they relate to your previous studies and future goals. (Max 1 page)
• Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above). Translations into English or Swedish if the original document is not issued in one of these languages.
• One representative publication or technical report. For longer documents, please provide a summary (abstract) and a web link to the full text.
• Two academic reference contacts.
• A research proposal, see link.

Other information

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about the processing of personal data in the recruitment process please read here.

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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.