JADS PhD in Simplifying Deep Learning Algorithms (SimplifAI) 1,0 FTE

Eindhoven University of Technology
January 10, 2023
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Offerd Salary:€2.541
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JADS PhD in Simplifying Deep Learning Algorithms (SimplifAI) 1,0 FTE

Position

PhD-student

Irène Curie Fellowship

No

Department(s)

Mathematics and Computer Science

Institutes and others

JADS Den Bosch

FTE

1,0

Date off

10/01/2023

Reference number

V32.6145

Job description

Are you passionate about deep learning (DL) and modern machine learning (ML) techniques? Are you intrigued by understanding how artificial intelligence (AI) models make predictions and inspired by developing to make them fair and responsible? Are you eager to contribute to transforming the Dutch and European industry towards implementing responsible AI solutions? If your answer “yes” to these questions, you might be our next PhD who will develop novel techniques to simplify complex AI models based on deep learning. Your challenge is to simplify the DL models to improve their explainability and ensure the fairness of the decisions.

JobDescription

AI-driven business innovation is crucial in many industries, which, nowadays, often depend on the use of deep learning . Furthermore, it is important to be at the forefront of creating responsible AI solutions that are fair, transparent and societally acceptable. Overparameterization is at the core of the success of deep learning algorithms. For example, Google's recently developed language model called Switch Transformer has 1.6 trillion free parameters. Although over-parameterization is beneficial to the training and subsequent generalization performance of deep learning algorithms, the resulting models lack transparency, are not robust to adversarial attacks and waste resources due to excessive training times. In this project, you will develop methods to mitigate these problems. The scientific challenge is to develop, evaluate, and validate simplified versions of existing over- parameterized deep learning algorithms, which will be evaluated in terms of transparency, fairness, robustness and resource consumption. A set of guidelines will be defined to identify the most suitable simplification methods and the metrics to apply in practice. A very important part of the work is developing methods for Fairness Quantification to ensure the algorithms' solutions will not have disparate impact to certain groups, based on attributes like but not limited to gender, race, religion, color, age, and their covariates.

As the PhD working on this challenge, you will become part of the Innovation Center for Artificial Intelligence (ICAI) Lab on Responsible AI in which KPN and JADS scientists work together develop transparent, privacy aware, and personalized AI solutions for businesses. You will also be part of the Computational Intelligence for Decision Support Lab at JADS, collaborating with other PhDs working in the Data Analytics Unit. In this diverse, inclusive and interdisciplinary environment, you are expected to collaborate closely with different stakeholders from KPN, academia and research institutes.

Job requirements
  • A master's degree (or an equivalent university degree) in artificial intelligence, data science, computer science or an equivalent quantitative field.
  • A research oriented attitude.
  • Ability to work in a team while also taking a pro-active attitude to drive your own research and its potential applications in collaboration with KPN and other stakeholders.
  • Fluent in spoken and written English (C1 level).
  • Conditions of employment

    Being appointed at JADS provides a meaningful job in a dynamic and ambitious community of two universities and startups.

    As a PhD Student at JADS you will have a full-time employment for a total of four years, with an intermediate evaluation after nine months. JADS offers excellent employment conditions with attention to flexibility and (personal) development and attractive fringe benefits. The gross monthly salary is in accordance with the Collective Labor Agreement for Dutch Universities (€2.541 in the first year up to €3.247 in the final year). You are entitled to a vacation allowance of 8% and a year-end bonus of 8.3% of your gross annual income. If you work 40 hours per week, you will receive 41 paid days of leave per year. PhD Students from outside the Netherlands may qualify for a tax-free allowance of 30% of their taxable salary if they meet the relevant conditions. The university applies for this allowance on their behalf. JADS will provide assistance in finding suitable accommodation.

    To develop your teaching skills, you will spend 10% of your employment on supervising EngD candidates and Master Thesis students involved in the same research domain. To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students.

    Next to that we offer all kinds of facilities and arrangements to maintain an optimal balance between work and private life. All employees of the university are covered by the so-called General Pension Fund for Public Employers (Stichting Pensioenfonds ABP).

    JADS values an open and inclusive culture. We embrace diversity and encourage the mutual integration of groups of employees and students. We focus on creating equal opportunities for all our employees and students so that everyone feels at home in our university community. You will be appointed via Eindhoven University of Technology. Please visit Conditions of employment TU/e Working at Eindhoven University of Technology (tue.nl) for more information on the employment conditions.

    Information and application

    More information

    Do you recognize yourself in this profile and would you like to know more? Please contact prof.dr.ir. U. Kaymak, e-mail u.kaymakatJADS.nl or +31 40 247 2793.

    For information about terms of employment, please contact Marielle van Gerven, HR Advisor, e-mail HRatjads.nl or +31 40 247 3699.

    Application

    We invite you to submit a complete application by using the 'apply now'-button on this page. The application should include a:

  • Cover letter in which you describe your motivation and qualifications for the position.
  • Curriculum vitae, including a list of your publications and the contact information of three references.
  • Brief description of your MSc thesis.
  • We look forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled.

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