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PhD candidate Causality-inspired Machine Learning

Faculty of Science – Informatics Institute

PhD candidate Causality-inspired Machine Learning
Publicatiedatum 28 januari 2021
Sluitingsdatum 15 april 2021
Opleidingsniveau Master's degree
Functieomvang 38 hours per week
Salarisindicatie €2,395 to €3,061 gross per month
Vacaturenummer 21-058

Are you interested in applying ideas from causal inference in machine learning research? The Intelligent Data Engineering Lab at the University of Amsterdam (UvA) is seeking a PhD candidate in causality-inspired machine learning (ML), i.e. the application of ideas from causality to different areas of ML, under the supervision of Dr Sara Magliacane.

As powerful as today’s AI systems are, nearly all of them are only able to see correlations - they can find patterns and apparent relationships in data, and use these patterns to make predictions and decisions. However, correlation is not causation, e.g., an expensive drug may appear to cure a disease until it is discovered that it is only prescribed to patients from more affluent backgrounds that have access to better healthcare.

In a world that is increasingly reliant on AI algorithms for mission-critical decisions, an AI that cannot distinguish between correlation and causation can lead to poor decision making, inefficiency and unfairness. Questions like, “Would I have been hired if I was a different gender?” or “Why was my credit application denied?” require a fundamental understanding of causality, as does the application of an AI system developed for one context (e.g., a movie recommendation algorithm trained to target a student population) to a different context (e.g., targeting the general public).

What are you going to do?

The focus of this PhD position is on how we can use insights from causal inference (a field with an extensive history in statistics, epidemiology and computer science) to improve machine learning algorithms? In particular, we are looking for PhD students that are interested in exploring the connections between causal inference, transfer learning and active learning.

While recent works have shown that causal insights may help in identifying features that transfer across different context, even in some apparently hopeless cases -- for example, when the new context is substantially different in many aspects from the original context and where there are no examples (labels) in the new context -- many of these methods still consider toy examples and leave many open questions on how to implement these insights in a real-world system.

You will be joining the INtelligent Data Engineering Lab (INDE Lab). While most ML starts with an abundant set of fairly clean data, one of the lab’s aims is to tackle machine learning problems in which the data is heterogeneous, noisy, missing or with few labels. The lab is situated within the larger Amsterdam data science and artificial intelligence ecosystem and values practice-informed and interdisciplinary research and outreach.

What do we require?

  • Master’s degree in Machine Learning, Statistics, Computer Science, Mathematics, or a related field;
  • English fluency, both written and spoken;
  • experience in programming and software development, in particular Python, R or C+, and possibly scientific computing or data science tools;
  • a passion for fundamental research and theoretical underpinnings of machine learning.

Candidates with a background in causal inference or transfer learning are preferred.

Our offer

A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The salary will be €2,395 to €3,061 (scale P) gross per month, based on a fulltime contract (38 hours a week).In addition there is a 8% holiday allowance and 8.3% end-of-year bonus. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Dutch Universities is applicable, including a solid pension scheme (ABP), a maximum of 41 days of annual leave based on a 40 hours work week, paid sick leave, maternity and paternity leave.

Are you curious about our extensive package of secondary employment benefits like our excellent opportunities for study and development? Take a look here.

Questions?

Do you have questions about this vacancy? Or do you want to know more about our organisation? Please contact:

About the Faculty of Science and the Informatics Institute

The Faculty of Science has a student body of around 7,000, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The mission of the Informatics Institute is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.

Job application

The UvA is an equal-opportunity employer. We prioritise diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.

Do you recognize yourself in the job profile? Then we look forward to receiving your application by 15 April 2021. You may apply online by using the link below.

Applications in .pdf should include:

  • a motivation letter, including a description of your research interests and an explanation for why you are applying for this position (at most two pages);
  • a CV, including a list of publications,
  • a list of all Master-level modules you have taken, with an official transcript of grades;
  • a link to a writing sample available online, such as a Master’s thesis, a term paper, or a publication (in case of joint authorship, please clearly indicate your own contribution);
  • the names, affiliations, and email addresses of two or (at most) three people we can act as references for you.

We will invite potential candidates for interviews starting from 30 April 2021.

No agencies please

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