Research Associate in Data Science (Large Scale Text Mining & Machine Learning)
- Employer
- Global Academy Jobs
- Location
- United Kingdom
- Closing date
- Jan 19, 2017
View more
- Sector
- Science, Computer Science and IT, Computer Science, General Computing
- Hours
- Full Time
- Organization Type
- University and College
- Jobseeker Type
- Academic (e.g. 'Lecturer')
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Job Details
Based in the Department of Computer Science, we are looking for a skilled developer of research software in the areas of large-scale text mining, natural language processing and machine learning, to join a team funded by the ERC grant “ThinkBIG”. The goal of the project is to develop tools and applications in the big data area, and analyse large corpora, building on our existing research. The position starts as soon as possible with funding up to 28 February 2019.
You will contribute to develop and extend a software infrastructure for the analysis of content from the WWW, newspapers and social media, their integration with other information sources, and the creation of new tools for the acquisition and analysis of large quantities of data. This is a position for an experienced data scientist with a strong background in computer science and software engineering, research training in Artificial Intelligence and software development experience. Background in statistical machine learning applied to text is essential. We require strong software skills in Java, and valuable experience in scaling software to big-data applications, operating on several million documents. You will have a strong academic background in computer science or computer engineering and research training, a relevant PhD is essential. Experience with GPUs, noSQL databases, and Deep Learning is desirable.
*Applicants should submit a sample of code (preferably Java) written by you which shows your best work in the creation of reusable, maintainable code in a group environment. Please select a sample no larger than 5 classes.
*While the job application should be done online via the university submission system, the sample of code (alone) should be sent to this email address: code.for.vacancy@gmail.com.
This post is being offered on a full time, open ended contract with funding up to February 2019.
Informal enquiries can be made to: Professor Nello Cristianini Nello.Cristianini@bristol.ac.uk
Closing date Midnight Thursday 19 January 2017.
Interviews will take place week commencing 30 January 2017.
You will contribute to develop and extend a software infrastructure for the analysis of content from the WWW, newspapers and social media, their integration with other information sources, and the creation of new tools for the acquisition and analysis of large quantities of data. This is a position for an experienced data scientist with a strong background in computer science and software engineering, research training in Artificial Intelligence and software development experience. Background in statistical machine learning applied to text is essential. We require strong software skills in Java, and valuable experience in scaling software to big-data applications, operating on several million documents. You will have a strong academic background in computer science or computer engineering and research training, a relevant PhD is essential. Experience with GPUs, noSQL databases, and Deep Learning is desirable.
*Applicants should submit a sample of code (preferably Java) written by you which shows your best work in the creation of reusable, maintainable code in a group environment. Please select a sample no larger than 5 classes.
*While the job application should be done online via the university submission system, the sample of code (alone) should be sent to this email address: code.for.vacancy@gmail.com.
This post is being offered on a full time, open ended contract with funding up to February 2019.
Informal enquiries can be made to: Professor Nello Cristianini Nello.Cristianini@bristol.ac.uk
Closing date Midnight Thursday 19 January 2017.
Interviews will take place week commencing 30 January 2017.
Company
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