Postdoc Research Fellow on Learning Algorithms for Missing and Faulty Data
Job offer posted on 17 june 2022
DesCartes Program (Work Package 2) is looking for two Postdocs (Research Fellow) on Learning Algorithms for Missing and Faulty Data
The DesCartes programme is developing a hybrid AI, combining Learning, Knowledge and Reasoning, which has good properties (need for less resources and data, security, robustness, fairness, respect for privacy, ethics), and demonstrated on industrial applications of the smart city (digital energy, monitoring of structures, air traffic control).
The program brings together 80 permanent researchers (half from France, half from Singapore), with the support of large industrial groups (Thales SG, EDF SG, ESI group, CETIM Matcor, ARIA etc.).
The research will take place mainly in Singapore, at the premises of CNRS@CREATE, with a competitive salary and generous funding for missions.
Read more about the DesCartes program here.
WP2 is hiring a postdoctoral research fellow interested in learning algorithms for missing and faulty data.
The main objective is to deal with real-world scenarios in which there are various restrictions and limitations on the data and the access to this data, or when data is large and fast moving, such as in data streams. This can take the form of, e.g:
- limited or throttled access to data, due to various factors such as API limitations, service-level agreements for accessing data, privacy issues
- missing data, due to faulty sensor data, or opt-outs for privacy reasons, or selection bias
- fast moving data, such as those arriving in streams or time-series data
In this context, the objective is to study methods to keep statistical guarantees on the data in the presence of missing and faulty data, by using a combination of the tools used in dimensionality reduction and sketching, and the statistical tools used to deal with missing data. In addition, an important part of the postdoctoral researcher task is to design and implement prototypes applicable in practice for the theoretical methods studied – notably sensor placement and fusion.
The postdoctoral fellow will be based in the CNRS@CREATE office and will be financially supported by DesCartes Program. She / he will have the opportunity to collaborate with/co-advise PhDs student in this area of research.
EXPERIENCE & QUALIFICATIONS
Ph.D. in computer science, computer engineering, machine learning, statistics, math, data science. She / he must have a strong proficiency in programming.
A good publication record in premier Computer Science / Machine Learning / AI conferences or journals.
- Data mining
- Stream data mining
- Probabilistic data processing
- Machine learning
FURTHER INFORMATION & CONTACT
Salary range: 6000-7200 (Research Fellow)
Workplace Address: CREATE Tower (NUS Campus), 1 Create Way #08-01 Singapore 138602
Please send a short cover letter describing your suitability for the position, detailed CV with academic ranking (if any) and publication list, a concise description of research interests and future plans, and academic transcripts to:
Prof. Arnab BHATTACHARYYA
Prof. Silviu MANIU
We will begin reviewing applications for the positions immediately.