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The ubiquity of sensor, computing, communication, and storage technologies provides us with access to previously unknown amounts of data—Big Data. It has revolutionized research communities and their scientific methodologies and innovated the approaches to knowledge and theory building, validation, and exploitation in the Sciences and the Humanities. With the foundation of a Linnaeus University Center on “Data Intensive Sciences and Applications” (DISA, https://lnu.se/disa) in Jan 2017, Big Data has officially become a research profile at Linnaeus University.
The advertised position will be physically placed Kalmar in the Software and Information Quality and eHealth groups. The research focuses on how clinical data can be used to improve quality, support processes reengineering and clinical development in healthcare. Our vision is to provide tools and services created from data that can help developers of healthcare operations, national clinical databases and decision support systems as well as clinicians. These tools and services will be based on statistical analyses, machine learning, optimization, etc. The research required is highly relevant for academia, health care and industry. Most of the work will be conducted in collaboration with health care. The Electronic Health Record (EHR) systems continue to expand. This means a massive and increasing volume of electronically stored data in the health sector. Access to these “real world data” from real-life patients (in contrast to data only from clinical trials) will increase the knowledge about patient characteristics and treatment patterns.
The work will be supervised by Assoc. Prof. Martin Carlsson, MD, PhD, and co-supervised by Prof. Welf Löwe and Assistant Prof. Lisa Ericson.
Field of subject for the position: Computer Science with specialization on eHealth
Placement: Department of Computer Science, Faculty of Technology, Växjö and eHealth Institute, Faculty of Health and Life Sciences, Kalmar, Sweden
The focus of this advertised PhD position and the corresponding research project is on how we can use large quantities of data to improve how we develop software and documentation as well as increase the quality of it. The research will be performed within DISA, funded by Linnaeus University. We will gather and analyze data, build and train models, and evaluate them.
Duties consist mainly of the following:
Graduate studies in the field of Computer Science, with a doctoral degree as the goal. The PhD thesis should be completed and defended within the official appointment duration of five years (4 years of graduate studies, 1 year of departmental tasks).
Research in the field computer science, machine learning, and optimization. The position is part of DISA and its subproject eHealth.
Regularly present intermediate research results at international conferences and workshops, and publish them in conference proceedings and journals.
Qualifications: see Lnu.se
Please contact the PI of the DISA subproject on eHealth Prof. Göran Petersson, email@example.com or the DISA research coordinator Prof. Welf Löwe, firstname.lastname@example.org, +46 76 760 36 62.
Head of department, Assoc.-Prof. Jesper Andersson, +46 470 708460, email@example.com. HR-partner, Carina Axelsson, +46 470 708507, firstname.lastname@example.org
Welcome to apply online no later than 2017-06-01. The application must include a cover letter (with a motivation why the candidate wants to pursue this PhD project), a resume and the contact information of two referees. In addition, a link to the candidate’s Master’s thesis should be provided.
Linnaeus University has the ambition to utilize the qualities that an even gender distribution and diversity brings to the organization.
Please apply by clicking on the "Apply" button at the bottom of the ad. Applicants are requested to the application resolving CV, cover letter , a copy of a relevant essay , grades and certificates and other relevant documents. The applicant also requested to submit with their application a proposed research plan within the current area of research. All documents must be attached to digital in the application. The application and other documents shall be marked with the reference number. All documents cited must be received by the University no later than 24.00 on the closing day.