PhD candidate Self-aware AI systems
- Vacancy number
- Function type
- PhD positions
- Hours (in fte)
- External/ internal
- Placed on
- 01 October 2019
- Closing date
- 30 October 2019
The Faculty of Science, Leiden Institute of Advanced Computer Science (LIACS), is looking for a
PhD candidate Self-aware AI systems
We offer a 4 year fully funded PhD position at the ADA research group, LIACS, Leiden University, supervised by Holger Hoos and Jan van Rijn. For AI systems to be trustworthy, they need to signal clearly when they “get out of their depth”, i.e., when their output (information, advice, actions) should be treated with caution or becomes entirely unreliable. For example, a configurator can configure a SAT solver to handle a ‘stream’ of SAT instances. However, once the new instances do no longer resemble the instances under which the solver was configured, performance might degrade and ideally the solver should be reconfigured.
In this project, we will develop methods capable of detecting whether the trained system is no longer up to date, signaling users when this is the case. There is an obvious trade-off between the additional cost of running an outdated system on the new instances, versus the cost to reconfigure the system to better perform on the new instances. Moreover, we aim to identify locations in the meta-feature space where EPMs (more general: AutoML systems) work poorly (e.g., due to lack of training instances, ambiguous training instances) and produce instance generators that can fill these gaps.
A more elaborate version of this description can be found in this PDF. There is funding for a PhD student (4 years); the position will depend on the experience of the successful candidate. The project will be embedded in the Automated Design of Algorithms group at the Leiden Institute of Advanced Computer Science. The group is headed by Professor Holger Hoos, and can be found at http://ada.liacs.nl/.
- Conduct original and novel research in the field of human-guided data science;
- Publish scientific articles in international journals and conferences;
- Write a dissertation.
- A MSc degree in Computer Science, Statistics, Data Science, Artificial Intelligence, or a related field;
- Good knowledge of and interest in data mining, machine learning, and statistics;
- Knowledge of Bayesian Optimization, Bandit methods and/or AutoML is a plus;
- Creative thinking and highly motivated to do foundational machine learning research;
- Good programming skills;
- Excellent proficiency in English;
- Excellent grades and good reference letters.
The Faculty of Science is a world-class faculty where staff and students work together in a dynamic international environment. Our people are driven by curiosity to expand fundamental knowledge and to look beyond the borders of their own discipline. The research carried out at the Faculty of Science is diverse, ranging from mathematics, artificial intelligence, computer science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental sciences. The faculty has grown strongly in recent years and now has more than 1,300 staff and almost 4,000 students. We are located at the heart of Leiden’s Bio Science Park, one of Europe’s biggest science parks, where university and business life come together. For more information: http://www.science.leidenuniv.nl.
The Leiden Institute of Advanced Computer Science (LIACS) is the Artificial Intelligence and Computer Science Institute in the Faculty of Science of Leiden University. We offer courses at the Bachelor and Master of Science level in Artificial Intelligence, Computer Science, ICT in Business, Media Technology, and Bioinformatics. According to an independent research visitation, we are one of the foremost computer science departments of the Netherlands. We strive for excellence in a caring institute, where excellence, fun, and diversity go hand in hand. We offer a clear and inviting career path to young and talented scientists with the ambition to grow. For more information about LIACS: http://www.cs.leiden.edu.
Terms and conditions
We offer a full-time temporary position for initially one year. After a positive evaluation of the progress of the thesis, personal capabilities and compatibility the appointment will be extended by a further three years. Salary range from € 2,325.- to € 2,972.- gross per month (pay scale P in accordance with the Collective Labour Agreement for Dutch Universities). All our PhD students are embedded in the Leiden University Graduate School of Science www.graduateschools.leidenuniv.nl. Our graduate school offers several PhD training courses at three levels: professional courses, skills training and personal effectiveness. In addition, advanced courses to deepen scientific knowledge are offered by the research school.
Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses (8.3%), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside the Netherlands may be eligible for a substantial tax break.
Leiden University is strongly committed to diversity within its community and especially welcomes applications from members of underrepresented groups. We wish to reflect society both in age, gender and culture, as we believe that this would optimize the dynamics in our organization. Therefore, we support and understand the need for a work/life/family balance and consequent varying working hours and places. In the Netherlands, a maternity allowance is standard for 16 weeks. Child care is available at and near the Bio Science Park.
Inquiries can be made to Jan van Rijn, assistant professor, email: email@example.com.
To apply for this vacancy, please send an email to Jan van Rijn, email: firstname.lastname@example.org. Please ensure that you attach the following additional documents quoting the vacancy number:
- Curriculum vitae;
- Motivation letter;
- MSc degree and grade list;
- MSc thesis;
- One to three references.
Only applications received no later than 30 October 2019 can be considered.