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Postdoc Job in Causal Representation Learning at the KTH, Sweden 2022


Postdoc Job in Causal Representation Learning is available for doctoral degree candidates in Statistics, machine learning at the EECS, KTH Royal Institute of Technology, Sweden 2022

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General Info

Position: Postdoc
No. of Positions: 1
Research Field: ,
Deadline to Apply: Expired
Joining Date: ASAP
Contract Period: 2 Years
Salary: According to standard norms


KTH Royal Institute of Technology, Sweden


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Qualification Details


  • A doctoral degree or an equivalent foreign degree, in Statistics, machine learning, or a related field. This eligibility requirement must be met no later than the time the employment decision is made
  • Research experience of using or developing statistical methods, with solid programming skills
  • We are searching for a person with research expertise and a publication record, with a high motivation to work and excel in an interdisciplinary team

Preferred qualifications

  • A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
  • We appreciate a track record showing collaborative skills, independence and teaching abilities
  • Awareness of diversity and equal opportunity issues, with specific focus on gender equality

Great emphasis will be placed on personal competency

Responsibilities/Job Description

Deep neural networks have achieved outstanding success on prediction tasks in a supervised learning setting when enough labeled data is available. Yet, current AI systems are limited in their ability to understand the world around us, as shown in a limited ability to transfer and generalize between tasks.

In order to achieve the goal of designing and understanding intelligent machines, a key requirement is the ability to build latent generative models and learn from interventions and counterfactuals.  This corresponds to an interactive learning environment, where the agent can discover causal factors through interventions, observe their effects and assign credit to each of its actions.

The goal of this position is thus to investigate how one can learn causal models of data from a reasonable set of assumptions as well as the experimental design of performing interventions and acquiring interventional data efficiently.

In this project, you will be involved in state-of-the-art machine learning research from the beginning and provide you with an opportunity to get started immediately with your topic. Our group is one of the few worldwide that successfully combines causality and deep learning with downstream applications from robotics to healthcare.

Our research is driven by real-world challenges with the potential for high societal impact and our work covers a wide spectrum between theory and application, with plenty of flexibility to adjust projects to your preferences. However, either a very strong theoretical background or experience with the common deep learning frameworks/software engineering skills is required.

How to Apply?

Application Method: Online Application
Ref. No.: J-2022-0594

Application Procedure

The application must include:

  • CV including relevant professional experience and knowledge.
  • Copy of certificates for prior academic education as degree, diploma and transcript of grades. Translations into English or Swedish if the original documents have not been issued in any of these languages. 
  • Brief account of your academic interests, why you are interested in this position, and how this relates to your previous studies and future goals. Max two pages long.

About the Employer:

Note or Other details


  • A position at a leading technical university that generates knowledge and skills for a sustainable future
  • Engaged and ambitious colleagues along with a creative, international and dynamic working environment
  • Mentorship in machine learning from leading experts
  • A creative role that combines a high degree of independence with mentorship and close interactions with other team members
  • Opportunity to develop cutting-edge statistical modeling methods to solve important real-world challenges, with potential for high impact discoveries
  • A possibility to pursue collaborative projects locally and internationally, and develop an international network and profile as a researcher
  • A supportive lab environment including mentorship for future career steps
  • Works in Stockholm, in close proximity to nature
  • Help to relocate and be settled in Sweden and at KTH

Read more about what it is like to work at KTH

Trade union representatives

You will find contact information to trade union representatives at KTH's webbpage.

About the employment

The position offered is for, at the most, two years.

A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.


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

We firmly decline all contact with staffing and recruitment agencies and job ad salespersons. Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.

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