PhD Projects in Big Data Analytics on Food Supply Chain Data

DTU Compute
Wednesday 01 Mar 17

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Apply no later than 31 March 2017
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DTU Compute’s section for Statistics and Data Analysis and section for Cognitive Systems, would like to invite applications for a 3-year PhD position starting 1 May. The project will be associated to the Innovation Foundation Denmark societal partnership “DABAI Danish Center for Big Data Analytics Driven Innovation”. The partnership is formed by the Computer Science departments of the Technical University of Denmark, Aarhus University, and University of Copenhagen, and the Alexandra Institute in collaboration with key businesses and public authorities to promote big data analytics. 

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.                                       

Project Description
The PhD-project will focus on research and implementation of “Big Data Analytics with special emphasis on Food Supply Chain data”. The project’s vision is demonstration of the advantage and efficiency of using big data analytical methods on such data. The research effort will require a high degree of interaction with relevant stakeholders along the food supply chain. As a first step data sources must be identified and described – especially with regard to uniqueness of these to the domain in question. Together with other members of the team relevant Big Data functionalities must then be carefully tailored and the businesses helped to deploy these. Analysis and quantification of the methods’ potential should then be described.   

Candidates must have a master degree in computational science and engineering, applied mathematics/statistics, machine learning, or engineering, or equivalent academic qualifications. Preference will be given to candidates who can document sound experience in statistics / machine learning and collaboration with external stakeholders, business partners or organizations. Experience in “data wrangling” is considered positively. Furthermore, good command of the English language is essential. Good command of 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 professors Bjarne Ersbøll and Lars Kai Hansen.  

We offer
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
Further information concerning the project can be obtained from Bjarne Ersbøll  

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 31 March 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)
  • CV
  • 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