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PhD fellow in Applied Geometry and Stochastic Analysis

Department of Computer Science (DIKU), Faculty of Science at University of Copenhagen is offering a PhD scholarship in applied geometry and stochastic analysis commencing 1 September 2018 or as soon as possible thereafter.  
 
Description of the scientific environment  
The Image section at DIKU hosts experts in fields including nonlinear statistics, applied differential geometry, shape modelling, image analysis & processing, computer vision, computer simulation, and machine learning. Their work ranges from theoretical analyses, over algorithm development, to solving concrete problems for science, industry, and society. Biomedical imaging is a central application area, including neuroimaging. The section contributes to the theory of image analysis by studying nonlinear statistics, variational problems, and geometry on manifolds and metric spaces. The section conducts core machine learning research, including deep learning, transfer learning, online learning, kernel methods, stochastic optimization, and concentration of measure inequalities. Furthermore, information retrieval methods are considered. For further information, please visit http://www.diku.dk/english/research/imagesection/ 
 
Project description  
The PhD student will focus on modelling stochastic variation in nonlinear geometries, Lie group theory, and geometric mechanics. The project will have both theoretical focus on construction, existence, and analysis of stochastic processes in nonlinear spaces; applied focus on stochastic shape modelling and statistics of shape; and numerical focus on implementation of simulation and inference algorithms. When disease processes influence the anatomy of organs, e.g. change of brain shape as a result of neurodegenerative disease, the shape variation can be captured from medical scans and analyzed, for example within the Large Deformation Diffemorphic Metric Mapping (LDDMM) framework. The changing shape is here represented by an element of a Riemannian manifold of diffeomorphisms, and statistical analysis of the data is therefore influenced by the curvature of the diffeomorphism manifold. One concrete goal of the project is to develop stochastic models and estimation algorithms for non-linear LDDMM inspired models. The PhD student will be part of the Centre for Stochastic Geometry and Advanced Bioimaging (CSGB, http://csgb.dk).  
 
The applicant must have documented experience in aspects of differential geometry, stochastic analysis, and/or theoretical statistics/machine learning. The project will require computer implementation of the developed numerical algorithms.  
 
Principal supervisor is Associate Professor Stefan Sommer, Department of Computer Science, sommer@di.ku.dk, Direct Phone: +4521179125.  
 
Job description  
The position is available for a 3-year period and your key tasks as a PhD student at SCIENCE are:  
  • To manage and carry through your research project  
  • Attend PhD courses  
  • Write scientific articles and your PhD thesis  
  • Teach and disseminate your research  
  • To stay at an external research institution for a few months, preferably abroad  
  • Work for the department  
Formal requirements  
Applicants should hold an MSc degree in Mathematics, Computer Science, Statistics or equivalent MSc education with good results and good English skills. As criteria for the assessment of your qualifications emphasis will also be laid on previous publications (if any) and relevant work experience.  
 
Terms of employment  
The position is covered by the Memorandum on Job Structure for Academic Staff.  
 
Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.  
 
The starting salary is currently at a minimum DKK 317.459 including annual supplement (+ pension up to DKK 43.852). Negotiation for salary supplement is possible.  
 
Application Procedure  
The application, in English, must be submitted electronically by clicking APPLY NOW below.  
 
Please include  
  • Cover Letter  
  • CV  
  • Diploma and transcripts of records (BSc and MSc)  
  • Other information for consideration, e.g. list of publications (if any),  
  • Full contact details (Name, address, telephone & email) of 1-3 professional referees  
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.  
 
The deadline for applications is 17 June 2018 23:59 GMT +2.  
 
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. Afterwards an assessment committee will be appointed to evaluate the selected applications. The applicants will be notified of the composition of the committee and the final selection of a successful candidate will be made by the Head of Department, based on the recommendations of the assessment committee and the interview committee.  
 
The main criterion for selection will be the research potential of the applicant and the above mentioned skills. The successful candidate will then be requested to formally apply for enrolment as a PhD student at the PhD school of Science. You can read more about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.  
 
Job interviews will be in week 31.
 
Questions  
For specific information about the PhD scholarship, please contact the principal supervisor Associate Professor Stefan Sommer, Department of Computer Science, sommer@di.ku.dk, Direct Phone: +4521179125  
 
General information about PhD programmes at SCIENCE is available at http://www.science.ku.dk/phd.  
 
 
 
APPLY NOW

Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

Info

Application deadline: 17-06-2018
Employment start: 01-09-2018
Department/Location: Datalogisk Institut

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