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Position: Research & Development Specialist in machine learning (M/F)
Institution: University of Luxembourg
Department: Interdisciplinary Centre for Security, Reliability and Trust (SnT)
Location: Luxembourg City, Luxembourg
Duties: We offer a “Research & Development Specialist” position to conduct applied research in the area of anomaly detection on sensor data. The successful candidate will join the SEDAN research team and will carry out R&D on the following topics: Machine learning (supervised and unsupervised learning). Big data management
Requirements: The candidate should possess an MSc degree or equivalent in Computer Science, Electronic Engineering or Applied Mathematics. The ideal candidate should have knowledge and experience in the following topics: Strong programming skills in C/C++, Python and SQL Strong knowledge of Machine Learning principles and tools A good knowledge of Statistics and Probability A good knowledge in data modelling and ETL development Language Skills: Fluent written and verbal communication skills in English are required
   
Text: UOL02559 21-Dec-2018 Company Text The University of Luxembourg is a multilingual, international research University. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from Master holders in the general area of machine learning. SnT is carrying out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. The Centre is currently expanding its research activities and is seeking highly motivated research associates who wish to pursue research in close cooperation with our partners. For further information you may check: www.securityandtrust.lu and https://wwwen.uni.lu/snt/research/sedan . The University of Luxembourg is looking for its Interdisciplinary Centre of Security and Trust (SNT) for a : Research & Development Specialist in machine learning (M/F) Ref: 50013824 - (R-STR-5023-00-B) Fixed Term Contract 1 year (CDD), full-time 40 hrs/week Number of positions: 1 Start day: Early 2019 upon agreement Your Role We offer a “ Research & Development Specialist” position to conduct applied research in the area of anomaly detection on sensor data . The successful candidate will join the SEDAN research team lead by Dr. Habil Radu State and will carry out R&D on the following topics : Machine learning (supervised and unsupervised learning). Big data management. The position holder will be required to perform the following tasks: Carrying out applied research in the predefined areas Providing support in setting up and running experiments in the Sedan laboratory For further information, please contact us jorge.meira@uni.lu or Radu.State@uni.lu . Your Profile Qualification: The candidate should possess an MSc degree or equivalent in Computer Science, Electronic Engineering or Applied Mathematics. Experience : The ideal candidate should have knowledge and experience in the following topics: Strong programming skills in C/C , Python and SQL Strong knowledge of Machine Learning principles and tools A good knowledge of Statistics and Probability A good knowledge in data modelling and ETL development Language Skills: Fluent written and verbal communication skills in English are required. For further information, please contact Jorge.meira@uni.lu or radu.state@uni.lu We offer The University offers a one-year (may be extended) employment fixed term contract, pending satisfaction of progress milestones (CDD), on full time basis (40hrs/week). The University offers highly competitive salaries and is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created research Centre. Further Information Applications, written in English should be submitted online and should include: Curriculum Vitae (including your contact address, work experience, publications) Cover letter indicating the areas of interest and your motivation Contact information for 3 referees All qualified individuals are encouraged to apply. Deadline for applications: December 21 st , 2018. Early submission is encouraged, applications will be processed upon arrival.
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