Laure Berti-Equille
2018-11-23 12:15:03 UTC
Data Quality-As-A-Service : Computing, Learning, and Querying Data Quality Indicators
* Position: Post-Doctoral fellow
* Time commitment: Full-time
* Starting date: Flexible, beginning from Feb 2019 or thereafter until Sept. 2019
* Duration: 12 months
* Indicative salary: depending on experience from 1,980€ to 2,320€ net per month (2,460€ to 2,890€ gross per month) with social security benefits
* Hosting lab: LIS Lab (CNRS UMR 7020), Aix-Marseille University, Marseille, France
* How to apply: Send your complete CV including a full publication list (and if possible a link to your PhD thesis) to:
***@lis-lab.fr and ***@lis-lab.fr
The candidate will participate to the extension of a data science platform dedicated to enhance the quality of healthcare data. The first step concerns prototyping a library of user-defined functions and machine-learning based algorithms for computing data quality indicators and their integration into this platform for real-world healthcare applications. The second step is to extend a query langage (SPARQL or SQL) to query data with declaring constraints on their quality. The work will be carried out in the context of QualiHealth, a multi-partner project recently funded by ANR (the French Agency for Research) and the creation of the new line of research initiatives in Data Science and AI at LIS Lab.
* The main missions are:
(i) Research on user-defined functions for data quality profiling of healthcare data;
(ii) Designing learning algorithms to discover data quality rules;
(iii) Prototyping and testing the query language extension for declaring, manipulating and learning data quality indicators and quality constraints;
(iv) Integration and interfacing with the platform.
* Required Profile:
◦ PhD in Computer Science
◦ Experience in machine learning and complex data analysis and/or data management
◦ Programming skills in Python
◦ Skills on big-data platforms (Hadoop/Spark)
◦ Good written and verbal communication skills
_______________________________________________
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* Position: Post-Doctoral fellow
* Time commitment: Full-time
* Starting date: Flexible, beginning from Feb 2019 or thereafter until Sept. 2019
* Duration: 12 months
* Indicative salary: depending on experience from 1,980€ to 2,320€ net per month (2,460€ to 2,890€ gross per month) with social security benefits
* Hosting lab: LIS Lab (CNRS UMR 7020), Aix-Marseille University, Marseille, France
* How to apply: Send your complete CV including a full publication list (and if possible a link to your PhD thesis) to:
***@lis-lab.fr and ***@lis-lab.fr
The candidate will participate to the extension of a data science platform dedicated to enhance the quality of healthcare data. The first step concerns prototyping a library of user-defined functions and machine-learning based algorithms for computing data quality indicators and their integration into this platform for real-world healthcare applications. The second step is to extend a query langage (SPARQL or SQL) to query data with declaring constraints on their quality. The work will be carried out in the context of QualiHealth, a multi-partner project recently funded by ANR (the French Agency for Research) and the creation of the new line of research initiatives in Data Science and AI at LIS Lab.
* The main missions are:
(i) Research on user-defined functions for data quality profiling of healthcare data;
(ii) Designing learning algorithms to discover data quality rules;
(iii) Prototyping and testing the query language extension for declaring, manipulating and learning data quality indicators and quality constraints;
(iv) Integration and interfacing with the platform.
* Required Profile:
◦ PhD in Computer Science
◦ Experience in machine learning and complex data analysis and/or data management
◦ Programming skills in Python
◦ Skills on big-data platforms (Hadoop/Spark)
◦ Good written and verbal communication skills
_______________________________________________
Please do not post msgs that are not relevant to the database community at large. Go to www.cs.wisc.edu/dbworld for guidelines and posting forms.
To unsubscribe, go to https://lists.cs.wisc.edu/mailman/listinfo/dbworld