PhD position in Applied Statistical Modelling of Stochastic Processes

torsdag 08 okt 20

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Frist 8. november 2020
Du kan søge om jobbet ved DTU Compute ved at udfylde den efterfølgende ansøgningsformular.

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A PhD position is offered at the Section for Statistics and Data Analysis, a part of the Department of Applied Mathematics and Computer Science (DTU Compute), at the Technical University of Denmark, starting 1 December 2020, or as soon as possible thereafter.

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 endeavor. 

The position is jointly financed through the Clinical Academic Group Acute CAG, DTU Section for Statistics and Data Analysis, University of Copenhagen and Region Zealand.

You will be working within the area of applied statistics, focusing on stochastic processes, network analysis, probability, machine learning and explorative statistics where appropriate, based on a data driven approach. Both method justification in terms of theoretical considerations and practical feasibility will be part of the work. 

The application area is chronical diseases in humans. With the increased longevity, the impact of chronical diseases on quality of life and public expenses, has increased over the last decades and will continue to do so. To obtain knowledge on which important factors that may cause, or may be associated with the development of, specific chronical diseases or clusters of conditions, when in life this happens, and if this appears to be changing over (calendar) time, are questions of major interest. The project will explore these matters, based on the case “chronical heart diseases and psychiatric diseases” as index diagnoses. 

Responsibilities and tasks
The project will concern applications to a database with longitudinal information on chronical diseases for Danish citizens. The project will concern combining information from several databases to obtain algorithmic diagnoses, and to model these in a longitudinal format – involving techniques such as Big Data tools, Hidden Markov Models and Survival Analysis with competing risks. 

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ou will, as a part of our project group, explore the data in a cross-disciplinary environment, which gathers experts within data science, probability, epidemiology and several medical professions, to synthesize the information for the benefit of society. The ultimate goal of the project, to which the PhD studies is expected to contribute, is to obtain a higher degree of understanding of the complex processes that governs the development of chronical diseases over time, and how these patterns may potentially be changed through medical and society preventive interventions. 

Qualifications
You should have a two-year master's degree (120 ECTS points) or equivalent academic qualifications within mathematics/statistics, computational science and engineering, engineering, or equivalent areas. Programming skills in at least one language such as R, Matlab, Python, Java or C is essential.  

You should, in addition, have an interest in seeing mathematics, probability, statistics and machine learning be put to beneficial use, and appreciate to operate among professionals from disciplines far from technical science, while still being placed in a department that has this as its main focus. 

  • You have the ability to acquire knowledge on how to deal with statistical modeling in Big Data.
  • You have knowledge on the specific challenges in handling longitudinal data, t. ex. Markov processes, Time series, Cox regression or similar.
  • You have excellent collaboration skills to match close collaboration and an interdisciplinary environment, and mastering of the English language, are essentials.
  • At the same time, you are innovative and enterprising, and enjoy sharing your ideas with colleagues.

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. 

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.  


Assessment
The assessment of the applicants will be made by Anders Stockmarr and Anne Frølich.    

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 from Associate Professor Anders Stockmarr, Technical University of Denmark, tel. +45 4525 3332, anst@dtu.dk, or Professor Anne Frølich, University of Copenhagen and Innovation and Research Centre for Multimorbidity, Slagelse hospital, Region Zealand, tel. + 45 2712 1622, anfro@sund.ku.dk

Further information concerning the application is available at the DTU Compute PhD homepage.

You can read more about DTU Compute at www.compute.dtu.dk/english

Application 
Applications must be submitted in English as one single PDF, and we must have your online application by 8 November 2020 (local time). To apply, 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)

Initial interviews are held on an ongoing basis. 

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, race, disability, religion or ethnic background are encouraged to apply. 

DTU Compute
DTU Compute is a unique and internationally recognized academic environment spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard - producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science.

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 12,000 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.