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Position: PhD Scholarship in Machine Learning based Perception for Inspection
Institution: Technical University of Denmark
Location: Kongens Lyngby, Lyngby‐Taarbæk Municipality, Denmark
Duties: The selected candidates will be responsible of the design and implementation of a machine learning -based and 3D-based perception system for the detection of faults in structures within the maritime industry. Expected contribution: Provide technical leadership in visual and ranging based machine learning systems for inspection (fault detection); Work within a strong, vibrant and cross-functional research team in real-life industrial projects; Develop, implement and test custom perception pipelines in a robotics framework; Contribute to the integration of work from different team members and industrial partners into a common solution; The research the selected candidate is expected to carry on could include dynamic modelling of aerial manipulators, control of physical interaction of floating-base systems, design of innovative mechanisms for aerial manipulation, AI for aerial manipulation, and the like; Applicants must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree; Additionally: Experience with open source robotic tools, such as ROS, would be an advantage; Hands on experience with hardware for sensing would be an advantage; Familiarity with design of convolutional neural networks architectures would be an advantage
Requirements: Applicants must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree; Additionally: Experience with open source robotic tools, such as ROS, would be an advantage; Hands on experience with hardware for sensing would be an advantage; Familiarity with design of convolutional neural networks architectures would be an advantage
   
Text: PhD Scholarship in Machine Learning based Perception for Inspection DTU Electrical Eng Share on Facebook Share on Twitter Share on Linkedin Wednesday 10 Jul 19 Apply for this job Apply no later than 26 July 2019 Apply for the job at DTU Electrical Eng by completing the following form. Apply online The Automation and Control Group at the Department of Electrical Engineering invites applicants for 3-years PhD position in the area of Machine Learning-based Perception for Inspection. The goal of this PhD project is to design, implement and test novel perception and machine learning methods for inspection in the maritime industry. The project will require understanding the application domain -which includes confined and highly reflective/dark areas- designing methods for the detection and classification of faults in vessel surfaces using Machine Learning (including but not limited to Deep Learning), producing perception to assist the navigation of an aerial vehicle, testing and validating the developed technologies in real-life applications. The selected candidate will have the opportunity to work closely with major players in the Danish maritime industry in the field of aerial inspection and will be part of a vibrant team with strong academic competences at DTU, where the position will be based. Cooperation with the other members of the project team and equal contribution to common building blocks of the developed system is foreseen. Assistant Professor Evangelos Boukas will supervise the selected student. The Automation and Control Group (AUT) at DTU Department of Electrical Engineering performs research in the technical sciences related to automation. A holistic and interdisciplinary approach is applied to the research within the field of robust autonomous systems and it is pursued as the key to the development of automation solutions able to reliably perform under uncertainty. The group research activities branch into three major directions: condition monitoring and decision support for safety critical systems; reconfigurable and self-learning systems; perception and situation awareness under uncertainty. AUT also holds strong expertise in perception for mobile autonomous robots through integration of smart sensor technologies, probabilistic methods and machine learning techniques. The available expertise in those areas is also outsourced for public and private consultancy. Responsibilities and tasks The selected candidates will be responsible of the design and implementation of a machine learning -based and 3D-based perception system for the detection of faults in structures within the maritime industry. Expected contribution: Provide technical leadership in visual and ranging based machine learning systems for inspection (fault detection) Work within a strong, vibrant and cross-functional research team in real-life industrial projects Develop, implement and test custom perception pipelines in a robotics framework Contribute to the integration of work from different team members and industrial partners into a common solution. The research the selected candidate is expected to carry on could include dynamic modelling of aerial manipulators, control of physical interaction of floating-base systems, design of innovative mechanisms for aerial manipulation, AI for aerial manipulation, and the like. Qualifications Applicants must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. Additionally: Experience with open source robotic tools, such as ROS, would be an advantage. Hands on experience with hardware for sensing would be an advantage. Familiarity with design of convolutional neural networks architectures would be an advantage. Approval and Enrolment The scholarships for the PhD degree are subject to academic approval, and the candidates will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide . Assessment Assessment of applications will be made by the supervisor together with other faculty members that will work closely to the PhD candidate. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. Salary and appointment terms The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. You can read more about career paths at DTU here . Further information Further information may be obtained by contacting Assistant Professor Evangelos Boukas, evbou@elektro.dtu.dk or 45 5290 1729. You can read more about Automation and Control Group at the Department of Electrical Engineering at www.elektro.dtu.dk /english . Application Please submit your online application no later than 26 July 2019 (local time) . Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file . The file must include: A letter motivating the application (cover letter) Curriculum vitae Grade transcripts and BSc/MSc diploma Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here ) Candidates may apply prior to obtaining their master's degree but cannot begin before having received it. Applications and enclosures received after the deadline will not be considered. All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. DTU Electrical Engineering educates students within electrical engineering technologies. We offer studies at BEng, BSc, MSc and PhD levels, and participate in joint international programmes. We conduct state-of-the-art research within antenna and microwave technology, robot technology, power and physical electronics, acoustic environment, electro-acoustics, electric power and energy. Our department has more than 200 members of staff. DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent university collaborating globally with business, industry, government and public agencies.
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