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The cloud-to-edge continuum, comprising a variety of computational resources from cloud data centers to resource-constrained devices at the network edge, offers many possibilities to optimize the deployment of machine learning (ML) applications. Different resources in the continuum may be associated with different advantages, e.g., cloud data centers offer practically unlimited compute capacity, whereas edge devices potentially offer low-latency communication with data sources, some nodes may offer special hardware optimized for ML operations (GPU, TPU), etc. Based on the needs of a specific ML application, network parameters, and the characteristics of available devices, different deployment strategies may be preferable, such as a cloud-only deployment, a deployment to a single edge device, a deployment over a set of edge devices, etc. The deployment may also be changed during the operation of a machine learning model, e.g., performing training in the cloud and inference at the edge.
Existing approaches to the deployment of ML in the cloud-to-edge continuum mainly focus on two aspects: maximizing accuracy (i.e., some measures for the ratio of correct inferences made by the ML model) and minimizing latency (i.e., the time needed to train the model or to perform inference). Optimizing other aspects of ML in the cloud-to-edge continuum is far less common. Two of the most prominent additional aspects that could be considered are:
Considerations of energy consumption and information security may impact deployment decisions, since different deployment options may have different influence on energy consumption and on information security. In addition, energy consumption and information security considerations may conflict with each other or with the more traditional accuracy and latency considerations. For example, processing data in an edge device may entail low latency, but may not be feasible because of the limited energy budget of the device, while moving the data to another device without energy limitations solves the energy problem but may lead to a security threat, which could be mitigated by anonymizing the data, but this may lower accuracy etc.
What are you going to do
You will develop new approaches for determining the optimal (or near-optimal) deployment of ML applications in the cloud-to-edge continuum, with a focus on energy and security considerations, while also accounting for accuracy and latency. Potential sub-goals:
The ultimate demonstrator for this project could be a model that can serve as a digital twin for such infrastructures, enabling informed decision making on a complex combination of risks and benefits with real-time adaptive response. Here, data access and sovereignty requirements can take extreme forms, which can lead to inconvenient and expensive solutions, like complete network separation. Embedded in the Complex Cyber Infrastructure group (CCI), you will become part of a large group of fellow PhD students and researchers working on connected topics.
What do you have to offer
Your experience and profile:
Fixed-term contract: 18 months.
Our offer
A temporary contract for 38 hours per week for the duration of four 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 four 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 gross monthly salary, based on 38 hours per week, ranges between €2,443 to €3,122 (scale P). This does not include 8% holiday allowance and 8,3% year-end allowance. 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:
Are you curious about our extensive package of secondary employment benefits like our excellent opportunities for study and development? Take a look here.
The University of Amsterdam is the largest university in the Netherlands, with the broadest spectrum of degree programmes. It is an intellectual hub with 39,000 students, 6,000 employees and 3,000 doctoral students who are all committed to a culture of inquiring minds and scientific excellence.
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 Complex Cyber Infrastructure (CCI) group is part of the Informatics Institute at the University of Amsterdam. CCI focuses on the complexity of man-made systems on all scales. This scale can be small, like the devices that you carry with you, or the apps they are running, or the communication protocols these apps use to interact. It can be also comprehensive, as in large systems such as data centres or multi-domain networks.
The complexity of these systems is caused by the fact that more and more cyber infrastructure - e.g. routers, switches, the cloud - is reprogrammable nowadays. This offers many possibilities, but it also makes the equipment more difficult to operate and less transparent. Further, there is the complexity of mapping in computational terms the data sharing requirements which are defined at societal level, through legislation, organizational policies, private data-sharing agreements, and consents.
CCI positions itself primarily in the Systems & Networking and Data Science research themes of the Informatics Institute.
Want to know more about our organisation? Read more about working at the University of Amsterdam.
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