PhD on AI-Enhanced Time-Critical Computing and Adaptation for Distributed Data-Centric Applications

We seek a Ph.D. student on the subject of 'AI-enhanced time-critical computing and adaptation for distributed data-centric applications.' The candidate will tackle the computing challenges in the use cases of digital twins, essential climate valuable workflows, and large-scale big data pipelines provided by research communities of environmental and earth sciences through ongoing projects LTER-LIFE, ENVRI-HUB next, and EVERSE. The candidate will research and develop AI-enhanced advanced algorithms for enabling quality critical applications, e.g., digital twins, on heteronomous computing infrastructure (e.g., from edge to hybrid and federated cloud environments), focusing on scheduling, optimization, performance diagnosis, and adaptation challenges of the application lifecycle from composition, deployment to runtime adaptation. The candidate will be encouraged to try state-of-the-art AI approaches to design the algorithms and obtain explainable findings.

The researchers will be embedded in the MultiScale Networked System (MNS) group, Informatics Institute at the University of Amsterdam. The candidate will work in an interdisciplinary team with domain scientists, modelers, and data curators to tackle the software challenges in developing virtual research environments and infrastructure services for constructing specific digital twins required by the ecological research domains.

What are you going to do?

The researcher will focus on the computing challenges in developing quality critical distributed data-centric applications. Working in an interdisciplinary team, the candidates will

• analyze the performance challenges of distributed data-centric applications provided by application domains
• review the state-of-the-art and technical gaps for developing quality critical distributed data-centric computing systems with a specific focus on AI and machine learning-based approaches,
• research,  develop, and validate scheduling, optimization, and adaptation algorithms for distributed data-centric computing systems via use cases and state-of-the-art baselines.

Your profile

The candidate should have a master degree in computer science or relevant disciplines and fluently speak and write English. Specifically, we are interested in people with:

• expertise in cloud computing, distributed and parallel computing, and data-centric applications,
• be familiar with AI (machine learning), big data, and data management techniques,
• be experienced in programming (using Java, Python or other languages),
• be willing to learn new theories, methods, and technologies when needed for the project.

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). 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 € 2,770 to € 3,539 (scale P). This does not include 8% holiday allowance and 8,3% year-end allowance. 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.

About us

The University of Amsterdam is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 30,000 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.

The MNS group  is part of the Systems and Security Lab (SNE), one of the three research clusters at the Informatics Institute. The group focuses its research on the fundamental architectural problems that arise from the interconnection of systems and data flows. We look at the emerging architectures that can support the operations of the future Internet. In particular, we focus on delivering secure and sustainable ICT services across multiple domains. Device programmability and virtualization play in this field an ever-increasing role in designing networks and ICT infrastructures. We address the interoperability challenges in supporting discovery, analysis and interoperation between heterogeneous complex infrastructures. Our vision is to build an effective ‘knowledge fiber’ to facilitate information discovery, integration, and reuse across distributed infrastructures.

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:

• Dr. Zhiming Zhao: z.zhao@uva.nl
• T: +31 641265121