Postdoc position in machine learning at Halmstad University, Sweden

Center for Applied Intelligent Systems Research, Halmstad University, Sweden is seeking to appoint a full-time Postdoctoral researcher in machine learning for two years. Salary is settled by negotiation, but is expected to be on the order of 3500€.

Description
The recruited person will be expected to teach up to 20{06fdc68f0c32a4bb4bc587245a8893a97471dc602b4e431d14a97651d507d6d7} and do research at least 80{06fdc68f0c32a4bb4bc587245a8893a97471dc602b4e431d14a97651d507d6d7}, within one or several scientific projects. Research activities will depend on competences and interests, but are expected to build upon our existing portfolio.

An example is the EVE project, which aims to extend the life of electric vehicles but (semi-)autonomously creating knowledge about their usage and degradation patterns from on-board sensor data. The research questions in this area are related to novel approaches exploiting Generative Adversarial Networks within the field of Transfer Learning. For example, how to estimate battery degradation in electric vehicles based on the historical usage data. Due to the rapid change in technology, there is not enough historical data about electric vehicles to achieve reliable accuracy and thus we need to find a relevant mapping of data between diesel and electromobility buses.

Another example, CAISR+ project, focuses on aware systems research and autonomous knowledge creation. By this we mean research on the design of systems that, as autonomously as possible, can construct knowledge from real life data created through the interaction between a system and its environment. Such systems should be able to handle events that are unknown at the time of design. One research question addresses machine activity recognition and representation learning using streaming data. Another research question concerns survivability analysis for complex machines with different components. The core challenge in this area is censoring, i.e., incomplete information about failures. We will address it using proxy events and using transfer learning.

Third example is the Battery Cortex project, where the work aims to provide electric vehicle OEMs and Fleet Operators with insights into quality, faults and anomalies of the battery packs, a critical component in EVs. It enables faster R&D iterations (vehicle improvements) and a continuous enhancement of the offer available to end-users, providing better insights to their EV assets.

All these research questions pose challenges that go beyond current state-of-the-art solutions in terms of information fusion from diverse data sources, identification of relevant factors, interpretability of data mining results, causal relation discovery and augmenting machine learning with expert knowledge.

AI and ML is an important part of our education. The recruited person will have an opportunity to advance Bachelor and Master level courses such as Artificial Intelligence, Learning Systems, Data Mining, Applied Data Mining, and Deep Learning. The person will also be involved in the Graduate professional development program (second-cycle courses targeted at the business sector). Finally, the recruited person is expected to participate in supervision of thesis projects for bachelor and master level students, as well as co-supervise PhD students.

Apply by 6th of December 2020 through our recruitment website https://hh.varbi.com/en/what:job/jobID:360644/iframeEmbedded:0/where:4

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Best wishes,
Slawomir Nowaczyk (Slawomir.Nowaczyk@hh.se), Professor in Machine Learning
Center for Applied Intelligent Systems Research, Halmstad University, Sweden
http://caisr.hh.se/Slawomir_Nowaczyk