The Core Facility Image Analysis headed by Dr.-Ing. Thorsten Falk has an opening for
a PhD position in the exciting interdisciplinary project "Smart process inspection (SPI)".
(Supervision: Prof. Thomas Brox)
We are seeking applicants with a strong interest in biomedical image analysis. Goal of the SPI project is to optimize bio-processes (e.g. maximize yield, ensure specified particle characteristics, ...) in large-scale bio-reactors. Our industrial partners already developed photo- and electro-optic probes that allow at-line and in situ process inspection in real time. Academic and industrial partners will use this hardware and provide challenging image data for automatic image analysis.
As scientific employee you will be filling a key position within the project and develop and apply machine learning for detection, tracking, classification and quantitative description of those particles. During the project you will be able to extend your knowledge in deep learning with convolutional neural networks and develop new architectures to solve the problem of end-to-end multi-instance segmentation and tracking of potentially overlapping objects in image sequences obtained through 2-D+t transillumination microscopy. Although the project mainly involves biological application, you will benefit from our close collaboration with the Computer Vision and Machine Learning labs giving you the opportunity to do bleeding-edge research in deep learning.
Beyond the scope of the project, the position includes supervision of students in lectures, seminars and lab courses offered by the Core Facility for Image Analysis or the Computer Vision Lab.
Successful candidates will join a young and dynamic research group, pursuing research that has strong impact in the field. The group's core research areas are image analysis for microscopical volumetric images and volumetric movies. In fundamental research the group works in close cooperation with the Computer Vision Group headed by Prof. Thomas Brox. On the application side many interdisciplinary collaborations exist with groups from biology and medicine.
The position is fully funded with a salary according to TV-L E13 (approximately 40k-43k Euro depending on proficiency). The position comes with direct supervision and support by Dr.-Ing Falk and Prof. Brox to enable completion of the thesis within 3 years. Funding for another year is available.
The University of Freiburg is one of the strongest research universities in Germany, with the Image Analysis Group and the Computer Vision Group being directly involved in the BIOSS cluster of excellence. Freiburg, the warmest spot in Germany, is located in the very southwest, and is only 30 minutes away from France and Switzerland. It is situated at the foot of the Blackforest and is close to the Alps with many possibilities for recreational activities.
Ideal candidates have an excellent degree (M.Sc. or equivalent) in Computer Science, Physics, or Mathematics. You must have a strong mathematical background and solid programming experience in C++ and ideally Matlab. Above all, you must have learned to work independently, have a strong motivation, interest for detailed analysis, and a distinct desire to learn. Prior experience in biomedical image analysis (especially image registration, tracking, variational methods and combinatorial optimization), computer vision or machine learning is advantageous. Fluency in English (both written and spoken) is required.
The University of Freiburg aims to increase the presence of women amongst its scientists, and qualified female candidates are strongly encouraged to apply. Physically challenged candidates with similar qualifications will be given special consideration.
The position is available from 1.09.2016 and will be filled as soon as an appropriate candidate is found. If you are interested, please send your complete application via e-mail at your earliest convenience. Detailed instructions are given below.
Contact: Dr.-Ing. Thorsten Falk
E-Mail: 
Date this offer was put online: 21.07.2016
Detailed instructions for applicants
Your application must comprise:Motivation letter
Your 1-2 page essay should contain the following details (not necessarily in this order):
- What is your background? In which fields have you studied/worked before and how do you think this can be useful for the present job?
- What attracts you to the field of computer vision?
- Which skills, what personality do you think can you contribute to the group? Which kind of person are you (e.g. creative, analytic, communicative, pragmatic, etc.) and what kind of work do you like most? What do you consider to be your 3 top strengths?
- Why do you wish to continue your career as a PhD student?
Curriculum Vitae
Send a classical tabular CV with your contact details, your date-of-birth, a current photograph, and all stages of education and employment. Begin and end dates should be at least month-accurate.
List of skills, awards, publications, hobbies
List your skills, especially proficiency in languages (including the level of proficiency), that you think might be useful for the job. Also list awards you might have got or papers you might have published already. You may also mention hobbies if you like.
Score records
Send copies of all your degrees and score records. If scores are neither compatible with the German nor the US system, give indication how your scores can be interpreted. If possible give evidence in which quantile of all graduates you are at your school.
Master thesis
Contact details of at least two academic references
If possible, please contact the references prior to listing their names. Sort them with the person who knows you best ranked first and give indication how each person is related to you. Try to select references who have supervised you while doing research (some project work, graduation thesis, etc.).
Your application can be in English or German. Please choose the language you are more familiar with.
Please send your application by e-mail only!
All documents must be in PDF format and must not be compressed. Combine all documents to a single PDF file or at least name the separate files appropriately.
If we find your application interesting, we will let you know within two weeks and ask you for further details (e.g., score records, an electronic copy of your Master thesis, contact details of two academic references).