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DTU Compute’s Sections for Statistics & Data Analysis and Dynamical Systems, would like to invite applications for two 3-year PhD position starting June 2017. The projects are financed by the Innovation Foundation Denmark as part of the project “SeaStatus – Innovative Technologies for Quantification of Sea Status”.
Our department DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavour.
DTU Compute strives to achieve research excellence in its basic science disciplines, to achieve technological leadership in research and innovation, and to address societal challenges in collaboration with partners at DTU and other academic institutions, nationally and internationally, and, equally important, with industry and organizations. We communicate and collaborate with leading centres and strategic partners in order to increase participation in major consortia.
DTU Compute plays a central role in education at all levels of the engineering programmes at DTU - both in terms of our scientific disciplines and our didactic innovation.
The project will assist industries and authorities to promote sustainable exploitation of marine ecosystem services by solving challenges in environmental management and providing profitable solutions for nature and business.
The SeaStatus project is a partnership formed by Department of Applied Mathematics and Computer Science at the Technical University of Denmark, the Department of Bioscience at Aarhus University, DHI, COWI, Rambøll, SVANA and the Danish Road Directorate.
This is a joint call for two positions. With the following descriptions:
Project 1: The project concerns data assimilation, and should provide the foundation for combining novel and traditional measurement techniques with ecosystem modelling, to improve the information basis for management, through establishing new routines for construction, standardization, integration and processing of large and differentiated data sets extracted from embedded information, for integration into model-based decision support tools. The information comes in different forms, such as on-line sensors, remote sensing, ferry-box data and underwater images. The successful candidate should develop routines to transform data into standardized formats in close collaboration with Project 2, and other parts of the SeaStatus project. Tools for the routine development may be (combinations of) rule-based algorithms, statistical image processing, low dimensional feature extraction, data mining and machine learning, deep learning techniques and traditional statistical and probabilistic surveillance techniques. A central part of the project is the documentation and evaluation of the developed algorithms.
Project 2: The project concerns statistical models for the time and/or spatial correlation that is inevitable in environmental data. The focus will be on the use of grey-box models based on stochastic (partial) differential equations and other statistical models in the modelling. Input data will come from Project 1 and other sources. The model development will be be performed in collaboration with marine experts within the project and also related to large mechanistic models that are developed in an other part of the project. A successful candidate should review existing stochastic models in this domain and make extensions thereof. Develop a framework for reducing large mechanistic models to stochastic grey-box models. A central part of the project is the documentation and evaluation of the developed models.
Candidates must have a master degree in mathematics/statistics, computational science and engineering, or engineering, or equivalent academic qualifications. Programming skills in at least one language such as R, Matlab, Java or C is essential.
For project 1 preference will be given to candidates who can document sound experience in applied statistics / machine learning and/or a documented record of algorithm Development.
For project 2 preference will be given to candidates who can document sound experience in applied statistics, using stochastic differential equations, and skills in R.
Furthermore, excellent collaboration skills and mastering of the English language is essential.
Mastering the Danish language will be considered an advantage.
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the DTU Compute PhD School Programme. For information about the general requirements for enrolment and the general planning of the scholarship studies, please see the DTU PhD Guide.
The assessment of the applicants will be made by Anders Stockmarr and Lasse Engbo Christiansen.
We offer an interesting and challenging job in an international environment focusing on education, research, scientific advice and innovation, which contribute to enhancing the economy and improving social welfare. We strive for academic excellence, collegial respect and freedom tempered by responsibility. The Technical University of Denmark (DTU) is a leading technical university in northern Europe and benchmarks with the best universities in the world.
Salary and appointment terms
The salary and appointment terms are consistent with the current rules for PhD degree students. The period of employment is 3 years.
Further information concerning the projects can be obtained from Anders Stockmarr and Lasse Engbo Christiansen.
Further information concerning the application is available at the DTU Compute PhD homepage or by contacting PhD coordinator Lene Matthisson +45 4525 3377.
Applications must be submitted in English as one single PDF, and we must have your online application by April 7th 2017. 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)
- documentation of a relevant completed M.Sc. or M.Eng.-degree
- course and grade list of bachelor and master degrees
- 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.
All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.
DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses in mathematics, statistics, and computer science to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees.
DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 5,800 advance science and technology to create innovative solutions that meet the demands of society; and our 10,600 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government, and public agencies