The University of Amsterdam (UvA) and the Bosch Group are opening a new collaborative research lab, Delta Lab 2. We are looking for two PhD candidates in machine learning to be a part of this collaboration. Research topics include generative models, geometric deep learning, causality, probabilistic modeling, Bayesian deep learning, uncertainty quantification, human-in-the-loop learning, and anomaly detection. Each project will be carried out in collaboration with Bosch research scientists. Delta Lab 2 is embedded within the Amsterdam Machine Learning Lab (AMLab) and the Computer Vision Lab (CV), two research groups within the UvA Informatics Institute. The lab will be part of the Innovation Center for Artificial Intelligence (ICAI), a Netherlands initiative focused on joint technology development between academia, industry and government in the area of artificial intelligence.

What are you going to do?

Tasks and responsibilities:

• Invent and evaluate novel methodologies for machine learning;
• Show that these methods have practical consequence;
• Present your research by contributing to international conferences, workshops, and journals;
• Assist in teaching activities: teaching course tutorials; supervising bachelor and master students;
• Actively participate in Delta Lab 2 activities, including visits to the Bosch headquarters in Renningen, Germany;
• Complete a PhD thesis within the appointed duration of four years.

 

Specifications

Your experience and profile:

• Master's degree in Machine Learning, Statistics, Computer Science, Mathematics, or a related field;
• Experience in programming and software development. Familiarity with Python and statistical computing libraries (e.g. NumPy, PyTorch, JAX) is preferred;
• Enthusiasm for the scientific process: formulating and conducting experiments, data collection and analysis, disseminating findings via writing and oral presentations;
• Ability to cooperate and work effectively within a team;
• Fluency in English, both written and spoken.

 

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). The preferred starting date is as soon as possible. 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 gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 2,541 in the first year to € 3,247 in the last year (scale P). UvA additionally offers an extensive package of secondary benefits, including 8% holiday allowance and a year-end bonus of 8.3%. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the '30% ruling', may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:

• 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
• Multiple courses to follow from our Teaching and Learning Centre;
• A complete educational program for PhD students;
• Multiple courses on topics such as leadership for academic staff;
• Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
• 7 weeks birth leave (partner leave) with 100% salary;
• Partly paid parental leave;
• The possibility to set up a workplace at home;
• A pension at ABP for which UvA pays two third part of the contribution;
• The possibility to follow courses to learn Dutch;
• Help with housing for a studio or small apartment when you're moving from abroad.

Are you curious to read more about our extensive package of secondary employment benefits, take a look here.

Faculty of Science

The University of Amsterdam (UvA) is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 42,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.

The Faculty of Science has a student body of around 8,000, as well as 1,800 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 (IvI) 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.

You will be working within the Amsterdam Machine Learning Lab (AMLab) which conducts research in the area of large scale modelling of complex data sources. This includes the development of new methods for probabilistic graphical models and non-parametric Bayesian models, the development of faster (approximate) inference and learning methods, deep learning, causal inference, reinforcement learning and multi-agent systems and the application of all of the above to large scale data domains in science and industry ('Big Data problems'). AMLab is co-directed by Max Welling and Jan-Willem van de Meent. AMLab positions itself in the AI research theme, and also with clear links to the Data Science theme of the Informatics Institute.

The mission of UvA-Bosch DELTA Lab (Deep Learning Technologies Amsterdam) is to perform world class research in the fundamentals of deep learning, with applications to automotive and computer vision. Researchers at UvA will collaborate with researchers at Bosch through an exchange program. Research topics include: Reinforcement Learning, Bayesian Deep Learning, Data Efficient Deep Learning, Multi-Modal Deep Learning, Generative and Unsupervised Deep Learning, Model Compression, and Adversarial Deep Learning.

Want to know more about our organisation? Read more about working at the University of Amsterdam.

Any questions?

Do you have any questions or do you require additional information? Please contact:

• E: Jan-Willem van de Meent, Associate Professor.