Universiteit Leiden

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Vacature

PhD candidate, Robustness Verification for Meta-learned Neural Networks

Vacature nummer
21-454
Categorie
PhD-posities
Doelgroep
Intern
Stad
Leiden
Publicatie datum
14 september 2021
Sluitingsdatum
30 oktober 2021 Nog 2 dagen om te solliciteren

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The Faculty of Science and Liacs Institute of Advanced Computer Science is looking for a

PhD candidate, Robustness Verification for Meta-learned Neural Networks

Vacancy number 21-454

Key responsibilities

Neural networks achieve state-of-the-art performance on many image-recognition tasks. Despite this enormous potential, it is widely acknowledged that neural networks also need large amounts of data and high GPU requirements to achieve this performance. Also, neural networks can be subject to adversarial attacks. The data- and GPU-related limitations can be addressed by meta-learning techniques, where such a neural network is pre-trained on similar tasks. This gives rise to few-shot learning, where neural networks have shown to be competitive if as few as five examples can be provided of a given class. The possibility of an adversarial attack is often addressed by neural network verification techniques that certify the robustness of a neural network. This Ph.D. trajectory will work on the intersection of meta-learning and neural network verification. 

Goal: The successful candidate will carry out research on the intersection of neural network verification and meta-learning. In particular, they will identify, construct and evaluate possible benchmarks that can be used across the research community. Additionally, we will develop techniques that combine the fundamental concepts and techniques from neural network verification and meta-learning. By applying AutoML techniques (e.g., Bayesian optimization, bandit methods) on meta-learning methods, we can search for hyperparameter configurations that do not only optimize for performance, but also take into account the robustness of a neural network.

Embedding: This project is part of the TAILOR network (https://tailor-network.eu/), a collaborative project containing the top research labs and industry partners across Europe (members from, e.g., Leiden University, University of Freiburg, INRIA). The candidate will be working with Prof. Dr. Holger Hoos and Dr. Jan N. van Rijn, from the Automated Design of Algorithms Research Group (ada.liacs.nl, LIACS, Leiden University). Our group has deep and broad expertise in all areas of machine learning relevant to this project and plays a key role in a large vibrant international research network; this will provide the candidate with ample opportunity to start a successful scientific career in one of the hottest areas of artificial intelligence.

Selection Criteria

  • We are looking for a graduated master student who majored in computer science or artificial intelligence;
  • Must have a track-record of algorithmic development, well-developed  programming skills and advanced knowledge in machine learning;
  • Demonstration of good research skills (through publications, teaching assistant positions) is an advantage.

Research at our faculty

The Faculty of Science is a world-class faculty where staff and students work together in a dynamic international environment. It is a faculty where personal and academic development are top priorities. Our people are committed to expand fundamental knowledge by curiosity and to look beyond the borders of their own discipline; their aim is to benefit science, and to make a contribution to addressing the major societal challenges of the future.

The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental sciences. The research activities are organised in eight institutes. These institutes offer eight bachelor’s and twelve master’s programmes. The faculty has grown strongly in recent years and now has more than 2.300 staff and almost 5,000 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, see the website of LIACS.

Terms and conditions 

We offer a  full-time 1 year term 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 € 2,434,-  to €3,111,-  gross per month (pay scale P in accordance with the Collective Labour Agreement for Dutch Universities).

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. For more information, see the website.

Graduate School

All our PhD students are embedded in the Leiden University Graduate School of Science.

 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.

Diversity

Leiden University is strongly committed to diversity within its community and especially welcomes applications from members of underrepresented groups.

Information

Enquiries can be made to  Jan N. van Rijn, Assistant Professor (j.n.van.rijn@liacs.leidenuniv.nl). If you have any questions about the procedure, please contact Maaike Veldkamp (m.j.d.veldkamp@liacs.leidenuniv.nl).

Applications

To apply for this vacancy, please send an email to jobs@liacs.leidenuniv.nl.

 Please ensure that you upload the following additional documents quoting the vacancy number:

  • Application Letter
  • Letter of recommendation from at least one established researcher
  • an example of your scientific writing (e.g., pointer to or copy of a publication or thesis)

Only applications received before October 31th, 2021 can be considered.

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