10 Postdoctoral Fellowship at Aalto University, Finland

The School of Arts, Design and Architecture (ARTS) is an institution of higher education for design, media, architecture, motion picture, art education and art. The current key areas of research are design, digital media, audiovisual representation, art, visual culture, welfare architecture and emerging technologies as well as urban planning and design. The school produces specialists and innovators of art, design and architecture with strong artistic and technical skills.

The Department of Mathematics and Systems Analysis is an international highly regarded academic community of more than 100 employees, with around 20 professors, 10 lecturers, 20 postdocs, and 60 doctoral candidates. Our department has a particularly welcoming culture, nurturing innovativeness and communication among our international and diverse faculty.

The Mathematical Physics Research Group in the Department of Mathematics and Systems Analysis at the School of Science is seeking two

Samuel Kaski’s research group Probabilistic Machine Learning is searching for postdocs to work on AI fundamentals in exciting projects. The work includes collaboration with ELLIS Institute Finland, the Finnish Center for Artificial Intelligence (FCAI), the Centre for AI Fundamentals at the University of Manchester,  the rest of ELLIS, and researchers from other fields.

Samuel Kaski is Professor of Computer Science in Aalto University and Professor of AI in the University of Manchester. He is Director of  ELLIS Institute Finland and the Finnish Center for Artificial Intelligence . His research group develops machine learning principles and methods focusing on a few key topics (see “Machine learning foundations” below), often working with researchers of other fields in new exciting applications (see the other topics below).

As a postdoctoral researcher, you will advance AI-based technologies for modelling, control, and optimisation of next-generation energy conversion systems. You will also have opportunities to contribute to our open-source computational tools, teach master-level courses, and advise doctoral students. Our strong industry connections will provide opportunities to see your research implemented in real-world applications.

Your primary task as a postdoc is to conduct research into quantum algorithms and information. You are expected to take an active role in advancing the research projects of the MQS group. Our recent research has focused on the theory and applications of variational quantum algorithms and quantum machine learning. We also have activity in quantum optics, so additional experience and interest in this topic is considered a definite advantage. Theoretical research into the capabilities of quantum computing and quantum advantage is also a prospective topic, especially in relation to cryptography. The exact research topics can be adjusted within the limits set by our current projects according to the interests of the applicant. Your goal in research will be to produce world-class results, in collaboration with the other group members, and publish them in high-impact journals.

In addition to research, you will also be expected to take part in the supervision of PhD students and the teaching activities of the research group.

Are you looking for a future industrial research position or a long-term academic career? Do you want to be part of building up research – preferably together with industrial partners? Do you like supervising students and participating in teaching? If you are a creative and analytical person and have a PhD in a field related to mathematical modeling and experience in optimizing industrial processes, this might be something for you!

We are looking for a postdoctoral researcher (“PostDoc”) to support the group and complement our research portfolio in the field of optimization. The work comprises combining theory and practice by investigating efficient ways to model and solve demanding industrial problems related to energy and sustainability. The decision levels mainly focus on planning and scheduling of production and associated supply chains, but an understanding of dynamic process models and life-cycle aspects is a big asset. In this work, you also need programming skills (e.g. Python, Julia) to merge concepts of chemical engineering, operations research and computer science, as you may also need to deploy machine learning to support data analytics and complex decision-making processes. Knowledge of modern SW-tools in the area of energy and sustainability is highly beneficial.

Your primary task will be to carry out research on the electrocatalytic upcycling of plastic waste. This involves: (a) Developing novel electrocatalysts based on multi-metallic structures for the conversion of plastic-derived monomers; (b) Characterizing these electrocatalysts using a range of techniques, including electron microscopy, diffraction, and other complementary methods; (c) Developing and applying analytical techniques, such as liquid chromatography, to identify and quantify reaction products.

The Structured and Stochastic Modeling Group, headed by Prof. Filip Elvander, conducts research in statistical signal processing, ranging from investigating fundamental properties of the mathematical descriptions of signals, to applied research in array signal processing. We are now looking for an outstanding Doctoral Researcher or Postdoctoral Researcher to join the group.

The research project is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available spectrum. In this environment, it is crucial to understand the spatio-temporal radio characteristics, i.e. what, when, and from where signals are transmitted. Applications of the envisioned research results include cognitive and adaptive spectrum use as well as localization of targets or signal sources in passive-sensing settings. This is central to future 6G wireless communications applications, where radio-frequency sensing and data transfer (ISAC) are integrated into the same devices.

The research project is part of a larger consortium, gathering world-class researchers in remote sensing with expertise ranging from estimation and optimization theory to hardware design. The specific topic of the project falls in the intersection of statistical signal processing and applied mathematics and is in particular concerned with optimal transport for inverse problems.

 We are seeking a motivated candidate to join our team. The successful applicant will be involved in the design, fabrication, and testing of functional thin film coatings.