Two years postdoctoral fellowship in data analysis and Machine learning in Paris
A postdoctoral fellow position on data analysis and machine learning is available at the University Paris-Est Créteil in the interdisplinary research laboratory LISSI and a startup with a huge potential in Genopole. The LISSI develops multi-disciplinary, theoretical and applied research in the field of Information Sciences and of Engineering with a strong orientation to healthcare applications. Genopole is the first biocluster in France dedicated entirely to biotherapies, research in genetics, genomics, post-genomics, xenobiology and the development of biotechnology industries.
The project will develop innovative machine learning and software tools to analyse data acquired from sensors installed on moving robots. This data is used for diagnosis and prognosis. More details about the project will be giving during the interview for confidentiality reasons. The selected candidate will have the chance to work in an interdisplanary team and a big consortium of data scientists, roboticists and mechanicians. He will have mentorship from an expert team of principal investigators. This two years of postdoctoral fellow can lead to a permanent contract.
Minimum to desired requirements:
·PhD in computer science, applied mathematics or electrical engineering, with a focus on machine learning.
·Experience in machine learning and data analysis
·Experience in computer vision and pattern recognition
·Demonstrated record of high-performance scientific programming with C++/python
·Demonstrated record of high-quality publications in the field
·Demonstrated analytical, verbal, and scientific writing skills
·Managing multiple tasks/projects at same time
·Experience in high performance computing, parallel computing and GPU CUDA programming would be a plus
·Experience in robotics would be a plus
The position is expected to be available starting April 2019. Applications will be continuously received until the position is filled. Applications and further questions regarding the position should be addressed to: Alice.firstname.lastname@example.org
(c) GdR 720 ISIS - CNRS - 2011-2020.