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Position: Post-Doctoral Position in Statistical Learning
Institution: Institut national de recherche en informatique et en automatique
Location: Rocquencourt, Île‐de‐France, France
Duties: The objective is to identify, amongst the specialized statistical (and/or machine learning) tools, those that could benefit the industry of assembling electronic boards with VI-Technology which brings here its expertise of inspection, and access to a wealth of information and images. Inspection machines are like sensors at different locations in a production site. They generate an astronomical amount of data. The goal is to explore whether this large data field can be better exploited with powerful statistical tools to significantly improve the understanding of interactions in the manufacturing process, and use this understanding to adjust the process quickly
Requirements: The applicant must be trained in data science, computer science or statistics. He/She moreover has the basis skills in at least in one of the software Matlab, R or python
   
Text: Post-doctoral position in Statistical Learning Contract Type: Post-doctoral positions (off campaign) Expiration date: 30-Sep-2017 About Inria and the job Inria, the French National Institute for computer science and applied mathematics, promotes “scientific excellence for technology transfer and society”. Graduates from the world’s top universities, Inria's 2,700 employees rise to the challenges of digital sciences. With its open, agile model, Inria is able to explore original approaches with its partners in industry and academia and provide an efficient response to the multidisciplinary and application challenges of the digital transformation. Inria is the source of many innovations that add value and create jobs. Mistis is a team developping statistical methodologies with various application fields : http://mistis.inrialpes.fr/index.html Mission Industry as we know it today will soon disappear. In the future, the machines which constitute the manufacturing process will communicate automatically as to optimize its performance as whole. Transmitted information essentially will be of statistical nature. The ambition of the project is to construct a new approach, looking at the entire production line, not machine by machine. The idea is to build a methodological and software solution that gives access to all the parameters, integrating all the logic of interactions between machines: A simple and intuitive "industry of the future" supervisor does not collect, but analyzes and drives to optimize, adapt, or reconfigure interoperability between machines. Job offer description The objective is to identify, amongst the specialized statistical (and / or machine learning) tools, those that could benefit the industry of assembling electronic boards with VI-Technology which brings here its expertise of inspection , and access to a wealth of information and images. Inspection machines are like sensors at different locations in a production site. They generate an astronomical amount of data. The goal is to explore whether this large data field can be better exploited with powerful statistical tools to significantly improve the understanding of interactions in the manufacturing process, and use this understanding to adjust the process quickly. Skills and profile The applicant must be trained in data science, computer science or statistics. He/She moreover has the basis skills in at least in one of the software Matlab, R or python. The knowledge of predictive methods (classification, neural networks, etc) or probabilistic graphical models will be a plus. Excellent interpersonal and editorial skills; Rigor, autonomy and technical curiosity to get involved in a multi-team project; Experience in project management would be a plus. Benefits •Restaurant on site •Financial participation for public transport •Social and sporting activities •French courses Additional Informations Security and defense procedure This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST). Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. Warning Applications must be submitted online on the Inria website. Processing applications submitted by other channels is not guaranteed. INRIA
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