EARLY STAGE RESEARCHER (PHD POSITION) NOBIAS

28 January 2020

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Interested?

Please supply the following documents in your application:

  • Detailed CV in Europass format (template at https://europass.cedefop.europa.eu/documents/curriculum-vitae/templates-instructions/templates/doc) in English, highlighting your achievements and fit to the applied position;
  • Scans of BSc and MSc transcripts, with certified translation in English (if the degree qualification is not in English or in the language of the hosting country); if you will only complete your Masters degree by the required starting date: please supply documentation of your achievements in the Masters programme so far;
  • A motivation letter in English, highlighting why you will be a good fit for the position and why you want to be a NoBIAS ESR to carry out this specific PhD;
  • Contact details or recommendation letters of two referees in English or in certified translation;
  • Proof of English skills (e.g., IELTS, TOEFL, Cambridge or equivalent). This is not required in case of native English speakers (i.e., English is your mother tongue)

Please apply NOW, since the position will be filled when a suitable candidate is found.
Applications will be processed according to the KU Leuven rules and in compliance with the general rules for projects in the H2020/Marie Skłodowska-Curie programmes.

Please contact Prof. Bettina Berendt (https://people.cs.kuleuven.be/~bettina.berendt/), the primary scientific supervisor of this PhD project, at bettina.berendt@kuleuven.be if you have any questions.

You can apply for this job no later than April 01, 2020 via the online application tool

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.

Apply before 01 April 2020

The Machine Learning group is part of the DTAI research group at the Department of Computer Science at KU Leuven. It follows an artificial intelligence approach to the analysis of data. It investigates a wide variety of machine learning, data mining and data analysis problems. This includes socially aware data mining, which recognizes the interaction between people and (especially data-analysis) technology in workplaces and other usage contexts, as well as the interrelations between this technology and other stakeholders who may be non-users. It integrates computational, cognitive, social, legal and economic considerations.

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Project

1. The project context: NoBIAS

"NoBIAS: Artificial Intelligence without Bias" is a project funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 860630.

NoBIAS aims at developing novel methods for AI-based decision making without bias by taking into account ethical and legal considerations in the design of technical solutions. The core objectives of NoBIAS are to understand legal, social and technical challenges of bias in AI-decision making, to counter them by developing fairness-aware algorithms, to automatically explain AI results, and to document the overall process for data provenance and transparency.
NoBIAS will train a cohort of 15 ESRs (Early-Stage Researchers) to address problems with bias through multi-disciplinary training and research in computer science, machine learning, artificial intelligence, law and social science. ESRs will acquire practical expertise in a variety of sectors from healthcare, telecommunication, finance, marketing, media, software, and legal consultancy to broadly foster legal compliance and innovation. Technical, interdisciplinary and soft skills will give ESRs a head start towards future leadership in industry, academia, or government.

2. Your tasks

The PhD project "Discovering biased representations of people" takes a computer-science and interdisciplinary approach to one of the key sources of bias in and through AI: how are people represented in AI models, what problems does this cause, and how can we solve or at least mitigate errors and resulting problems?

You will focus on representational adequacy, i.e., the extent to which data represent what is (legally and/or ethically) objectionable about bias. The project will develop a modelling language to integrate background knowledge, requirements engineering methods to elicit adequate representations, and composition methods to integrate different representations.

Profile

You have a Masters degree in Computer Science, Artificial Intelligence, or a similar discipline. You have strong data science skills. Skills in knowledge representation and other fields of AI are a plus. You care not only about AI, but also about the ethical dimension of informatics, and you are motivated to learning and taking a critical and interdisciplinary approach that values the social sciences while leveraging your computer scientist’s understanding and skills. Prior experience with topics with an ethical dimension is a plus (privacy/data protection, fairness/non-discrimination, dealing with bias and misinformation, …).

General eligibility criteria: To be eligible, the applicant must satisfy the mobility requirements of Marie Sk³odowska-Curie actions. At the time of recruitment, the potential candidate

  • "must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not taken into account ".
  • "be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree".

You work efficiently and reliably, independently as well as in teams. You have very good communication skills and scientific curiosity. Your English is very good. You are flexible and prepared to travel and to integrate into the local teams, while keeping a focus on your PhD and on delivering scientific and other project-related output.

We welcome all applicants, but specifically encourage people from traditionally under-represented groups to apply.

Applications that do not meet the eligibility criteria will not be considered.

Offer

You will hold a fully funded PhD position for up to three years. You will be part of a stimulating and dynamic environment of various European top-level universities and other institutions. You will be based at KU Leuven in Belgium, in the AI / machine learning group of the Department of Computer Science. On a regular basis, you will conduct research visits and secondments at several of the NoBIAS partner institutions, according to the individual career development plan. You will engage, throughout your PhD, at NoBIAS partner organizations across the EU, in disciplines including computer science, social sciences, and law. You will engage in the NoBIAS research activities and actively collaborate within the consortium. You will actively participate in the training programme offered by the NoBIAS ITN. You will work independently as well as in local and international teams, with a focus on producing excellent research as well as in learning and acting in real-life contexts of AI creation and deployment.
You start this position as soon as possible between 1 March and July 2020.