Two assistant professor positions

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Title Two assistant professor positions
Description Two assistant professor positions at CAISR, Halmstad University

Application deadlines: 13 & 20 October 2019

https://hh.varbi.com/se/what:job/jobID:287916/iframeEmbedded:0/where:4
https://hh.varbi.com/se/what:job/jobID:285183/iframeEmbedded:0/where:4

Event Date 2019/10/13
Post Date 2019/10/01

Two assistant professor positions at CAISR, Halmstad University
Application deadlines: 13 & 20 October 2019

https://hh.varbi.com/se/what:job/jobID:287916/iframeEmbedded:0/where:4
https://hh.varbi.com/se/what:job/jobID:285183/iframeEmbedded:0/where:4

Two Assistant Professor positions in Data Mining (in collaboration with healthcare and with industry)

CAISR, School of Information Technology, Halmstad University, Sweden

The Department of Intelligent Systems and Digital Design (ISDD) at Halmstad University (Sweden) is seeking to appoint a full-time Assistant professor in Information technology with focus on data mining and machine learning. Appointment as Assistant Professor is a qualifying appointment with the purpose to give the employee a possibility to promote to Associate Professor. Appointment as Assistant Professor is for four years.

The ISDD Department, has for a long time had a strong scientific output in AI, digital service innovation, data mining and machine learning, as well as excellent (and practical) results from its education programs involving intelligent systems. Its main focus is on aware intelligent systems that can be self-monitoring, can fuse heterogeneous information, and can communicate with humans and be aware of their intentions. The University has established a strong network of public sector and industry relationships, in which Alfa Laval AB is an important industrial partner. This recruitment is tightly connected to existing collaboration efforts between Halmstad University and Alfa Laval AB.

  • Work assignments

Self-monitoring of complex systems is regarded as an important task as it reduces costs and improves the reliability of such systems. Still, today the majority of diagnostic functions are created by human experts in a time-consuming and expensive process. One typical system delivered by Alfa Laval AB consists of multiple, partially similar separators (centrifuge machines that employ a high rotational speed to separate components of different densities) whose operation produces multivariate streaming data that is continuously collected but currently under-utilized. The candidate will work in close collaboration with Alfa Laval AB (in Stockholm-Tumba and Copenhagen) on developing data mining methods and algorithms to analyse such data and produce tools for fault detection. This can be achieved by comparing the operation of each machine against its own past behaviour and against a group of similar machines in order to identify faults and anomalies. In addition, the candidate will investigate how information extracted from the data can be combined with expert knowledge by interacting with domain experts, taking advantage of available a priori knowledge, explaining and justifying the solutions given, as well as accepting feedback and incorporating it into further processing.

The planned research activities build upon our existing research, including the abovementioned iMedA project, by addressing three research questions. First, how to create a meaningful and comprehensive representation of each patient based on comprehensive medical data. Second, how to predict different clinical outcomes (e.g., re-admissions) and non-clinical behaviors (e.g., medication non-adherence) using interpretable machine learning methods. Third, how to identify a selection of intervention strategies that are most appropriate for a particular patient, by combining both data-driven and knowledge driven approaches. The overall scope is to increase information driven care capabilities using ML on several data domains including EHR, financial, HR and other production generated data in order to create new insights. All three 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.

In CAISR (www.hh.se/caisr) we have long experience with very fruitful collaboration and relationship building between the University and companies. This position will follow the same general setup, with the assistant professor spending approximately two says on company premises in order to understand the inner working, the culture and the day-to-day operation. This is expected to lead to a deep relationship that allows us to coordinate on strategic level, where Hallandia V helps us shape future CAISR research directions. As a result, the collaboration will generate many new possibilities for joint projects and offer us an opportunity to increase our visibility. Given the strong research background of the Hallandia V company we also expect several high-level publications to be co-authored jointly.

Read more about Halmstad University at http://hh.se/english/discover/discoverhalmstaduniversity.9285.html

Apply on:
https://hh.varbi.com/se/what:job/jobID:287916/iframeEmbedded:0/where:4
https://hh.varbi.com/se/what:job/jobID:285183/iframeEmbedded:0/where:4