PhD Position/Research Assistant, Forensic Writer Identification using Machine Learning

Project Description

The Austrian Security Research Programme KIRAS supports national research projects whose results contribute to the security of all members of society. Currently we have multiple open projects funded by the KIRAS program. The focus of these projects is to develop technologies based on machine learning to assist law enforcement agencies. For this we cooperate with different government agencies like the Federal Ministry of the Interior and the Federal Ministry of Justice.

In course of the WRITE project we are developing an IT assisted search and comparison of handwritings using a machine learning methodology to expedite the identification of unknown writers by handwriting experts. Law enforcement agencies possess an extensive collection of handwritten documents. This includes for example documents belonging to open cases and reference samples from suspects and prisoners. Yet, these collections of documents can currently only be utilized to a limited extend, since for an identification of an unknown writer all documents have to be compared manually by handwriting experts. The goal of WRITE is a retrieval system is accurate enough to list documents from the same writer in the top 2% of the retrieved sorted list in 80% of the cases. The Referat Urkunden- & Handschriftenuntersuchung im Büro für Kriminaltechnik des Bundeskriminalamts in the Federal Ministry of the Interior (BMI) possesses a comprehensive collection of handwritten documents essential for such a development.

Job Description

You will work in a team of computer scientists from the Computer Vision Lab, forensic experts and software developers from the Cogvis Gmbh. Your goal will be to use state-of-the-art machine learning techniques like deep learning to develop a computer vision methodology. Other than the project requirements and common best practices you will be completely unrestricted as to which technologies you choose to solve the problems at hand. No more “use framework xyz and editor xyz and operating system wxy”!

You will get the chance to publish and present your results at international conferences and we will support and supervise you on your way to your PhD at the TU Wien.

Requirements

    • Experience with Python and Data Analytics
    • Masters’s degree in Computer Science, Mathematics, or similar
    • Preferably experience with Computer Vison applications and Machine Learning/Deep Learning
    • Bonus points if you already published a scientific paper

Contact: sab@cvl.tuwien.ac.at