Difference between revisions of "OpenPositions"
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| − | Currently, CAISR has | + | Currently, CAISR has one open position in Data Mining: |
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== Postdoctoral researcher in information technology, focus on data mining == | == Postdoctoral researcher in information technology, focus on data mining == | ||
| − | Application deadline: | + | Application deadline: 2018-01-21 |
==== Research focus ==== | ==== Research focus ==== | ||
| − | This two years full-time employment at the School of Information Technology, with a starting date as soon as possible, is linked to the Department of Intelligent Systems and Digital Design, a dynamic research environment with focus on aware intelligent systems. The subject expertise in the group is machine learning, data mining, signal analysis, mechatronics and digital service innovation. Mining of sensor data streams and medical records, big data analytics, self-monitoring, and deviation detection are examples of areas of particular interest for us. We have a very good track record of doing research in close collaboration with the Swedish industry and public sector. The department has about 30 MSEK annual research budget, with 13-16 PhD students and about 30 researchers with PhDs. The department hosts the Centre for Applied Intelligent Systems Research (CAISR). The latest annual report for CAISR is available at www.hh.se/caisr. | + | This *two years full-time employment* at the School of Information Technology, *with a starting date as soon as possible*, is linked to the Department of Intelligent Systems and Digital Design, a dynamic research environment with focus on aware intelligent systems. The subject expertise in the group is machine learning, data mining, signal analysis, mechatronics and digital service innovation. Mining of sensor data streams and medical records, big data analytics, self-monitoring, and deviation detection are examples of areas of particular interest for us. We have a very good track record of doing research in close collaboration with the Swedish industry and public sector. The department has about 30 MSEK annual research budget, with 13-16 PhD students and about 30 researchers with PhDs. The department hosts the Centre for Applied Intelligent Systems Research (CAISR). The latest annual report for CAISR is available at www.hh.se/caisr. |
| − | The PostDoc position is primarily funded by two research projects: 1) BIDAF (Big Data Analytics Framework for a Smart Society), a distributed research environment of Halmstad University, SICS Swedish ICT and Högskolan i Skövde | + | The PostDoc position is primarily funded by two research projects: 1) iMedA (Improving MEDication Adherence through Person Centered Care and Adaptive Interventions), collaboration between Halmstad University, Hallands Hospital and CGI; and 2) BIDAF (Big Data Analytics Framework for a Smart Society), a distributed research environment of Halmstad University, SICS Swedish ICT and Högskolan i Skövde. |
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| + | The iMedA project aims to improve medication adherence through an AI agent that supports doctor and patient in collaboratively understanding key individual concordance risk factors and designing an appropriate intervention plan. iMedA will then deliver the selected intervention through a mobile App and follow-up on its effectiveness in order to, over time, improve the system. The combination of person-centered care and self-management interventions will lead to significantly improved health outcomes and reduced healthcare costs. Improving patient health outcomes depends on predicting and understanding adherence on an individual level; providing adequate information to doctor and patient in order to mediate a collaborative treatment plan; and supporting the patient at home with adaptive interventions. Individual steps have been undertaken in research, there are however no studies nor commercial products that combine all three aspects using AI agents capable of improving the system over time. | ||
The BIDAF project aims to significantly further the research within massive data analysis, by means of statistical machine learning, in response to the increasing demand of retrieving value from data in all of society. Our research focuses on scalable algorithms that can leverage the distributed framework for efficient mining of knowledge from transient data streams. In particular, we aim to move from algorithms designed to exploit limited amounts of data for as much knowledge as possible towards algorithms designed to process large amounts of data efficiently, build models that are constrained in size, and provide end users with easy to understand and traceable results. | The BIDAF project aims to significantly further the research within massive data analysis, by means of statistical machine learning, in response to the increasing demand of retrieving value from data in all of society. Our research focuses on scalable algorithms that can leverage the distributed framework for efficient mining of knowledge from transient data streams. In particular, we aim to move from algorithms designed to exploit limited amounts of data for as much knowledge as possible towards algorithms designed to process large amounts of data efficiently, build models that are constrained in size, and provide end users with easy to understand and traceable results. | ||
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The unprecedented amount of data accessible today allows machine learning to focus on more descriptive and explanatory analysis. Users no longer pose well-formulated, concrete questions, but instead require the system to be capable of highlighting interesting aspects such as deviations, anomalies, relations and co-occurrences. It is almost effortless to generate data, while the cost of analysing it does not change. We will support continuous learning model, where the training and usage is not easily separated, and the system improves its performance all the time, taking advantage of new data as it arrives. An important aspect of the position is to find connections to other projects within CAISR and on identifying common problems and finding solutions applicable across multiple domains. | The unprecedented amount of data accessible today allows machine learning to focus on more descriptive and explanatory analysis. Users no longer pose well-formulated, concrete questions, but instead require the system to be capable of highlighting interesting aspects such as deviations, anomalies, relations and co-occurrences. It is almost effortless to generate data, while the cost of analysing it does not change. We will support continuous learning model, where the training and usage is not easily separated, and the system improves its performance all the time, taking advantage of new data as it arrives. An important aspect of the position is to find connections to other projects within CAISR and on identifying common problems and finding solutions applicable across multiple domains. | ||
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==== Application ==== | ==== Application ==== | ||
| − | Applications should be sent via Halmstad University's recruitment system MyNetwork (see link on this page). The last day to apply for the position is | + | Applications should be sent via Halmstad University's recruitment system MyNetwork (see link on this page). The last day to apply for the position is 2018-01-21. |
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The application package shall consist of: | The application package shall consist of: | ||
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Halmstad University prepares people for the future by creating values, driving innovation and developing society. Founded in 1983, the University has long been associated with new ways of thinking, relevant degree programmes and small student groups. Research at Halmstad University is internationally acclaimed as cutting-edge and with a multi-disciplinary approach. The University actively participates in social development through extensive and renowned collaboration with both the business and the public sector. | Halmstad University prepares people for the future by creating values, driving innovation and developing society. Founded in 1983, the University has long been associated with new ways of thinking, relevant degree programmes and small student groups. Research at Halmstad University is internationally acclaimed as cutting-edge and with a multi-disciplinary approach. The University actively participates in social development through extensive and renowned collaboration with both the business and the public sector. | ||
| − | The working language is English and no knowledge of Swedish is required to start working at the University. Also for daily life, English is spoken widely and Sweden has the highest English | + | The working language is English and no knowledge of Swedish is required to start working at the University. Also for daily life, English is spoken widely and Sweden has the highest English Proficiency index in the world. Of course, it’s advisable that the employee learn Swedish. Both the University and the local government provide extensive facilities. |
Halmstad is a popular summer destination located on the Swedish west coast. It is situated halfway between two cosmopolitan areas: the Copenhagen-Malmö-Lund area and the Gothenburg area, making it a well-connected, yet a pleasantly calm place to live. Halmstad can be reached by a direct train connection from the Copenhagen Kastrup Airport, as well as other local airports (e.g., Gothenburg Landvetter Airport, Halmstad, and Helsingborg/Ängelholm airports). | Halmstad is a popular summer destination located on the Swedish west coast. It is situated halfway between two cosmopolitan areas: the Copenhagen-Malmö-Lund area and the Gothenburg area, making it a well-connected, yet a pleasantly calm place to live. Halmstad can be reached by a direct train connection from the Copenhagen Kastrup Airport, as well as other local airports (e.g., Gothenburg Landvetter Airport, Halmstad, and Helsingborg/Ängelholm airports). | ||
| − | + | [https://hh.mynetworkglobal.com/se/what:job/jobID:182085/iframeEmbedded:0/where:4 Apply here] | |
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For more information on any of the positions, contact [[Antanas Verikas]] or [[Slawomir Nowaczyk]] | For more information on any of the positions, contact [[Antanas Verikas]] or [[Slawomir Nowaczyk]] | ||
Revision as of 22:34, 20 December 2017
Currently, CAISR has one open position in Data Mining:
Contents
Postdoctoral researcher in information technology, focus on data mining
Application deadline: 2018-01-21
Research focus
This *two years full-time employment* at the School of Information Technology, *with a starting date as soon as possible*, is linked to the Department of Intelligent Systems and Digital Design, a dynamic research environment with focus on aware intelligent systems. The subject expertise in the group is machine learning, data mining, signal analysis, mechatronics and digital service innovation. Mining of sensor data streams and medical records, big data analytics, self-monitoring, and deviation detection are examples of areas of particular interest for us. We have a very good track record of doing research in close collaboration with the Swedish industry and public sector. The department has about 30 MSEK annual research budget, with 13-16 PhD students and about 30 researchers with PhDs. The department hosts the Centre for Applied Intelligent Systems Research (CAISR). The latest annual report for CAISR is available at www.hh.se/caisr.
The PostDoc position is primarily funded by two research projects: 1) iMedA (Improving MEDication Adherence through Person Centered Care and Adaptive Interventions), collaboration between Halmstad University, Hallands Hospital and CGI; and 2) BIDAF (Big Data Analytics Framework for a Smart Society), a distributed research environment of Halmstad University, SICS Swedish ICT and Högskolan i Skövde.
The iMedA project aims to improve medication adherence through an AI agent that supports doctor and patient in collaboratively understanding key individual concordance risk factors and designing an appropriate intervention plan. iMedA will then deliver the selected intervention through a mobile App and follow-up on its effectiveness in order to, over time, improve the system. The combination of person-centered care and self-management interventions will lead to significantly improved health outcomes and reduced healthcare costs. Improving patient health outcomes depends on predicting and understanding adherence on an individual level; providing adequate information to doctor and patient in order to mediate a collaborative treatment plan; and supporting the patient at home with adaptive interventions. Individual steps have been undertaken in research, there are however no studies nor commercial products that combine all three aspects using AI agents capable of improving the system over time.
The BIDAF project aims to significantly further the research within massive data analysis, by means of statistical machine learning, in response to the increasing demand of retrieving value from data in all of society. Our research focuses on scalable algorithms that can leverage the distributed framework for efficient mining of knowledge from transient data streams. In particular, we aim to move from algorithms designed to exploit limited amounts of data for as much knowledge as possible towards algorithms designed to process large amounts of data efficiently, build models that are constrained in size, and provide end users with easy to understand and traceable results.
The unprecedented amount of data accessible today allows machine learning to focus on more descriptive and explanatory analysis. Users no longer pose well-formulated, concrete questions, but instead require the system to be capable of highlighting interesting aspects such as deviations, anomalies, relations and co-occurrences. It is almost effortless to generate data, while the cost of analysing it does not change. We will support continuous learning model, where the training and usage is not easily separated, and the system improves its performance all the time, taking advantage of new data as it arrives. An important aspect of the position is to find connections to other projects within CAISR and on identifying common problems and finding solutions applicable across multiple domains.
Principal duties
The selected candidate will become part of the very dynamic and international research environment at the Center for Applied Intelligent Systems Research (CAISR), at the School of Information Technology. For more information please see: http://caisr.hh.se/ The post as postdoctoral researcher is a qualifying appointment with the purpose to give the employee a possibility to develop its independence as researcher and to obtain merits that can lead to a competence for another post with higher eligibility requirements. As a postdoctoral researcher you are expected to be active in the research done within the research environment CAISR. The teaching load will be at most 20% of the time working hours. Furthermore, we expect you to take an active part in the continued development of the research environment and that you will take part in applying for research funding from various financiers, both in Sweden and abroad.
Qualification
The position is intended for someone with a recent PhD degree in Information Technology, Computer Science, Computer Engineering, or closely related fields. The research track record should demonstrate excellence in research areas such as machine learning and data mining. Strength in computer programming and/or applied mathematics is very welcome.
Salary
Salary is to be settled by negotiation. The application should include a statement of the salary level required by the candidate.
Application
Applications should be sent via Halmstad University's recruitment system MyNetwork (see link on this page). The last day to apply for the position is 2018-01-21.
The application package shall consist of:
1) a cover letter stating the purpose of the application and a brief statement of why you believe that your goals are well-matched with the goals of this position, together with a description of future research plans
2) a CV that includes at least
- a list of previous degrees, with dates and institutions
- a complete list of publications with 2-3 most relevant ones for this position marked
- a description of previous research and other work experience
3) contact information for at least three references.
General Information
Halmstad University prepares people for the future by creating values, driving innovation and developing society. Founded in 1983, the University has long been associated with new ways of thinking, relevant degree programmes and small student groups. Research at Halmstad University is internationally acclaimed as cutting-edge and with a multi-disciplinary approach. The University actively participates in social development through extensive and renowned collaboration with both the business and the public sector.
The working language is English and no knowledge of Swedish is required to start working at the University. Also for daily life, English is spoken widely and Sweden has the highest English Proficiency index in the world. Of course, it’s advisable that the employee learn Swedish. Both the University and the local government provide extensive facilities.
Halmstad is a popular summer destination located on the Swedish west coast. It is situated halfway between two cosmopolitan areas: the Copenhagen-Malmö-Lund area and the Gothenburg area, making it a well-connected, yet a pleasantly calm place to live. Halmstad can be reached by a direct train connection from the Copenhagen Kastrup Airport, as well as other local airports (e.g., Gothenburg Landvetter Airport, Halmstad, and Helsingborg/Ängelholm airports).
For more information on any of the positions, contact Antanas Verikas or Slawomir Nowaczyk
