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Position: PhD Position in Data Analytics in Production
Institution: Technical University of Denmark
Location: Kongens Lyngby, Lyngby‐Taarbæk Municipality, Denmark
Duties: During your PhD project, you will be part of a group of researchers in data analytics and have the chance to interact with individuals with similar research interests. The group is currently engaged in many industrial projects, which will allow you to observe various application cases of the methodological developments we are working on. The project will also involve another PhD candidate and a professor from NTNU with whom you will have the opportunity to collaborate to further your research. As a PhD candidate, you will have the opportunity to teach BSc/MSc students in our regularly offered courses in data analytics. You will also have the opportunities to develop your teaching skills in our distance learning and continuing education programs through short courses offered primarily for the industry
Requirements: You must have a master degree in engineering science or natural science or equivalent academic qualifications. You must have a very strong background in data analysis, mathematical modelling, and computing and if you have practical experience with large datasets and machine learning methods we highly encourage you to apply. Furthermore, prior knowledge in software packages such as R and Python as well as proficient coding skills will be required. You must be fluent in English, both speaking and writing with great communication and presentation skills
   
Text: PhD Position in Data Analytics in Production DTU Compute Share on Facebook Share on Twitter Share on Linkedin Tuesday 24 Mar 20 Apply for this job Apply no later than 1 June 2020 Apply for the job at DTU Compute by completing the following form. Apply online DTU Compute would like to invite applications for a 3-year PhD position starting September 1, 2020. The position is financed by DTU, and is part of the joint doctoral degree program together with the Norwegian University of Science and Technology (NTNU). The candidate is required to spend at least one year in total at each of the institutions. The successful candidate will be offered a three-year position. Project Description The term Big Data seems to be ubiquitous in many fields of applications and industrial production is no different. However, in production this can be somewhat misleading as it often refers to process data which is obtained through automated data collection schemes with minimal manual interference. Product related data is usually scarcer particularly in high volume production due to cost of inspection. This creates an imbalance in the amount of available data which can in times be quite substantial. Yet in many cases, predictive modeling relating process variables to product characteristics is sought after. Therefore it will be beneficial to guide the data collection schemes for product characteristics through a real time sampling methodology. This methodology should actively dictate when and how the new product data would be collected. In this project, we will investigate multivariate data analysis and process monitoring methods to trigger the need for product data collection when this approach detects out-of-the ordinary circumstances. The project will involve an industrial partner for immediate applications of developed methodologies. Opportunities During your PhD project, you will be part of a group of researchers in data analytics and have the chance to interact with individuals with similar research interests. The group is currently engaged in many industrial projects, which will allow you to observe various application cases of the methodological developments we are working on. The project will also involve another PhD candidate and a professor from NTNU with whom you will have the opportunity to collaborate to further your research. As a PhD candidate, you will have the opportunity to teach BSc/MSc students in our regularly offered courses in data analytics. You will also have the opportunities to develop your teaching skills in our distance learning and continuing education programs through short courses offered primarily for the industry. Requirements You must have a master degree in engineering science or natural science or equivalent academic qualifications. You must have a very strong background in data analysis, mathematical modelling, and computing and if you have practical experience with large datasets and machine learning methods we highly encourage you to apply. Furthermore, prior knowledge in software packages such as R and Python as well as proficient coding skills will be required. You must be fluent in English, both speaking and writing with great communication and presentation skills. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval. You will be enrolled in the DTU Compute PhD School as the host institute. For information about the general requirements for enrolment and the general planning of the scholarship studies, please see the DTU PhD Guide . Assessment The assessment of the applicants will be made by Associate Professor Murat Kulahci (DTU Compute) and Professor John Tyssedal (NTNU). 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 concerning the project can be obtained from Associate Professor Murat Kulahci at muku@dtu.dk . Further information concerning the application is available at the DTU Compute PhD homepage or by contacting PhD coordinator Lene Matthisson at 4525 3377 or lemat@dtu.dk . Application Applications must be submitted in English as one single PDF , and we must have your online application by 1 June 2020 (23:59 local time) . Please open the link in the red bar in the top of the page: "apply online" (“ansøg online”). Applications must include: Application (letter of motivation) CV (incl. list of publications or other research experience) Documentation of a relevant completed M.Sc. or M.Eng.-degree Course and grade list of bachelor and master degrees Calculation of the weighted grade average with course names translated to English (link here ) An example technical text you have written in English such as a report prepared for a course, a consulting project, or a published peer-reviewed scientific article. If one or more of the items requested above is missing, the application will be considered invalid. Applications and enclosures received after the deadline will not be considered. All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply. Compute conducts research and provides teaching in the fields of mathematics, modeling and computer science. The expanding mass of information and the increasingly complex use of advanced technology in society demand development of advanced computer based mathematical models and calculations. The unique skills of the department are in high demand in IT innovation and production. Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland. The Norwegian University of Science and Technology (NTNU) NTNU represents academic eminence in technology and the natural sciences as well as in other academic disciplines ranging from the social sciences, the arts, medicine, teacher education, architecture to fine art. The university employs about 4500 researchers and educators (41% women) and enrolls approximately 40,000 students. At the Department of Mathematical Sciences at NTNU, there are 58 full time faculty at the department (11 women), 20 postdoctoral fellows, and about 60 doctoral students. The department has five research groups: algebra, analysis, differential equations and numerical analysis, geometry and topology, and statistics.
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