Job ID: 2914
Job date: 2015-03-04
End Date:
Company : Blekinge Institute of Technology Country : Role : Postdoc
Job date: 2015-03-04
End Date:
Company : Blekinge Institute of Technology Country : Role : Postdoc
Job Description:
Work description:
The position includes primarily research (80%) in computer science with a focus on machine learning, data mining & knowledge discovery, and related areas. The position also includes teaching (20%) within the area, mainly at advanced level but also at basic level. The position also includes supervision of doctoral students and students at advanced level. The position is financed by a large research project, Scalable resource-efficient systems for big data analytics, where close collaboration with industry is key for the project execution. The duties also include performing and publishing research of high international quality as well as applying for external research grants.
About the research profile:
Data will be generated at an ever-increasing rate for the foreseeable future. Added value and cost savings can be obtained by analyzing big data streams. The analysis of large data sets requires scalable and high-performance computer systems. In order to stay competitive and to reduce consumption of energy and other resources, the next generation systems for scalable big data analytics need to be more resource-efficient. The research profile, Scalable resource-efficient systems for big data analytics, combines existing expertise in machine learning, data mining, and computer engineering to create new knowledge in the area of scalable resource-efficient systems for big data analytics. The value of the new knowledge will be demonstrated and evaluated in two application areas (decision support systems and image processing).
The needs and interests of our 11 industrial partners are grouped into industrial challenges. Based on these challenges and in cooperation with our partners we have defined initial sub-projects grouped into four research themes:
Research theme A: Big data analytics for decision supportResearch theme B: Big data analytics for image processingResearch theme C: Core technologies (machine learning)Research theme D: Foundations and enabling technologies
This research profile is in the center of the university's vision to be a globally attractive knowledge community within applied information technology and innovation for sustainable growth. The research group currently includes four full professors, two associate professors, four assistant professors, and a number of Ph.D. students. The mix of competences gives unique possibilities to develop new knowledge in the profile area. The profile includes a well-defined career advancement program and a visiting researcher program.
About the department:
The Department of Computer Science and Engineering (DIDD) was established on January 1, 2014. DIDD belongs to the Faculty of Computing and currently includes 36 staff members out of which 17 are senior researchers and 12 are PhD students. The department offers education and conducts research in computer science and computer engineering as well as related areas. The University profile is applied IT and innovation for sustainable development. The research and education at DIDD are completely aligned to this profile, and are conducted in close collaboration with partners from both the private and the public sector.
Application:
To submit your application, please click on the "APPLY" button.
The application documents shall comprise five parts:
Cover sheetAccount of scientific and educational workCV with annexesList of publicationsDocuments, maximum of 10
For more information, please refer to www.bth.se/jobb.
BTH is an equal opportunity employer, thus all applicants are welcome to apply.
Please submit your application, marked with the reference number for the position, by March 31, 2015 at the latest.
Additional Info:
[Click Here to Access the Original Job Post]
Work description:
The position includes primarily research (80%) in computer science with a focus on machine learning, data mining & knowledge discovery, and related areas. The position also includes teaching (20%) within the area, mainly at advanced level but also at basic level. The position also includes supervision of doctoral students and students at advanced level. The position is financed by a large research project, Scalable resource-efficient systems for big data analytics, where close collaboration with industry is key for the project execution. The duties also include performing and publishing research of high international quality as well as applying for external research grants.
About the research profile:
Data will be generated at an ever-increasing rate for the foreseeable future. Added value and cost savings can be obtained by analyzing big data streams. The analysis of large data sets requires scalable and high-performance computer systems. In order to stay competitive and to reduce consumption of energy and other resources, the next generation systems for scalable big data analytics need to be more resource-efficient. The research profile, Scalable resource-efficient systems for big data analytics, combines existing expertise in machine learning, data mining, and computer engineering to create new knowledge in the area of scalable resource-efficient systems for big data analytics. The value of the new knowledge will be demonstrated and evaluated in two application areas (decision support systems and image processing).
The needs and interests of our 11 industrial partners are grouped into industrial challenges. Based on these challenges and in cooperation with our partners we have defined initial sub-projects grouped into four research themes:
Research theme A: Big data analytics for decision supportResearch theme B: Big data analytics for image processingResearch theme C: Core technologies (machine learning)Research theme D: Foundations and enabling technologies
This research profile is in the center of the university's vision to be a globally attractive knowledge community within applied information technology and innovation for sustainable growth. The research group currently includes four full professors, two associate professors, four assistant professors, and a number of Ph.D. students. The mix of competences gives unique possibilities to develop new knowledge in the profile area. The profile includes a well-defined career advancement program and a visiting researcher program.
About the department:
The Department of Computer Science and Engineering (DIDD) was established on January 1, 2014. DIDD belongs to the Faculty of Computing and currently includes 36 staff members out of which 17 are senior researchers and 12 are PhD students. The department offers education and conducts research in computer science and computer engineering as well as related areas. The University profile is applied IT and innovation for sustainable development. The research and education at DIDD are completely aligned to this profile, and are conducted in close collaboration with partners from both the private and the public sector.
Application:
To submit your application, please click on the "APPLY" button.
The application documents shall comprise five parts:
Cover sheetAccount of scientific and educational workCV with annexesList of publicationsDocuments, maximum of 10
For more information, please refer to www.bth.se/jobb.
BTH is an equal opportunity employer, thus all applicants are welcome to apply.
Please submit your application, marked with the reference number for the position, by March 31, 2015 at the latest.
Skills :
Areas :
Additional Info:
[Click Here to Access the Original Job Post]