Difference between revisions of "OpenPositions"
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| − | There are no open positions at the moment. | + | <strike>There are no open positions at the moment.</strike> |
| − | + | == Post doctoral researcher in information technology with a focus on data mining == | |
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| − | + | === Deadline for applications: 2015-03-01 === | |
| − | + | A full-time employment for two years from April 2015, or as soon as possible thereafter. The position is mainly funded by the BIDAF (A Big Data Analytics Framework for a Smart Society) project, which is a distributed research environment between Högskolan i Halmstad, SICS Swedish ICT and Högskolan i Skövde, supported by the Swedish Knowledge Foundation (KKS). | |
| − | + | === Research focus: === | |
| + | The overall aim of BIDAF is 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 main way of extracting value from data is to capture the interesting aspects of it using a suitable model. The model is then used for detecting anomalies and trends, analysing key values, or making predictions. In the big data setting, however, one can create not one, but many useful models, focusing on different aspects of the data. We will develop new algorithms for building such sets of models and for ensuring sufficient diversity among them, as well as ways to combine them in flexible ways, for example into hierarchical structures of concepts and sub-concepts, or along time axis to distinguish permanent and time-limited patterns. | |
| − | + | The unprecedented amount of data accessible today allows ML 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), a part of Halmstad Embedded and Intelligent Systems Research (EIS) at the School of Information Technology. | ||
| − | The | + | 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 environments CAISR and EIS. 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 in 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: === | |
| + | The [http://www.hh.se/omhogskolan/jobbahososs/ledigaanstallningar/postdoctoralresearcherininformationtechnologywithafocusondatamining.65443418.html official announcement of the position], including details about how to apply, is available on the Halmstad University page. | ||
| − | + | For more information about the position please contact [[Slawomir Nowaczyk]] | |
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| − | For more information about the position please contact | ||
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Revision as of 18:29, 2 February 2015
There are no open positions at the moment.
Post doctoral researcher in information technology with a focus on data mining
Deadline for applications: 2015-03-01
A full-time employment for two years from April 2015, or as soon as possible thereafter. The position is mainly funded by the BIDAF (A Big Data Analytics Framework for a Smart Society) project, which is a distributed research environment between Högskolan i Halmstad, SICS Swedish ICT and Högskolan i Skövde, supported by the Swedish Knowledge Foundation (KKS).
Research focus:
The overall aim of BIDAF is 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 main way of extracting value from data is to capture the interesting aspects of it using a suitable model. The model is then used for detecting anomalies and trends, analysing key values, or making predictions. In the big data setting, however, one can create not one, but many useful models, focusing on different aspects of the data. We will develop new algorithms for building such sets of models and for ensuring sufficient diversity among them, as well as ways to combine them in flexible ways, for example into hierarchical structures of concepts and sub-concepts, or along time axis to distinguish permanent and time-limited patterns.
The unprecedented amount of data accessible today allows ML 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), a part of Halmstad Embedded and Intelligent Systems Research (EIS) at the School of Information Technology.
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 environments CAISR and EIS. 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 in 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:
The official announcement of the position, including details about how to apply, is available on the Halmstad University page.
For more information about the position please contact Slawomir Nowaczyk
