Johannes Gutenberg University Mainz (JGU) is one of the largest universities in Germany. Thanks to its location in the Rhine-Main science region, the university can unfold to its full potential and showcase its innovative power and dynamism. Its status as a comprehensive university allows for multidisciplinary learning and teaching and has great potential for internationally renowned, interdisciplinary research. Almost all of its institutes are located on a single campus close to the Mainz city center – creating a lively academic culture for researchers, teaching staff, and students from every continent.
The Data Mining group headed by Prof. Dr. Stefan Kramer at the Institute of Computer Science of Johannes Gutenberg University Mainz
2 Research Scientists
The Institute of Computer Science of JGU is specialized in data science and has many of its application projects in the life sciences. The data mining group of Prof. Kramer is internationally visible and active in both fields (see https://www.datamining.informatik.uni-mainz.de/stefan-kramer/).
Your tasks:
The successful applicant is expected to work on her or his PhD thesis.
The duration of the contract is determined by the BMBF project "Cluster for Atherothrombosis and Individualised Medicine (curATime)". The focus of curATime is atherosclerosis and atherothrombosis, the dominant causes of cardiovascular disease (CVD). AI will be used both for biomarker search and the development of innovative therapeutics for individually targeted treatment. The research is conducted in collaboration with, amongst others, TRON gGmbh (Translational Oncology Mainz), the University Medical Center of the University of Mainz, and Innoplexus AG, with access to unique data sets and knowledge bases. The two subprojects of curATime are concerned with cutting-edge topics from both the machine learning and the biomedical point view:
- curAIknow: the development of new knowledge-based machine learning techniques for use within the consortium. One source of knowledge is a very large, curated, biomedical knowledge graph.
- curAIheart: AI-based analysis of cine-loops of echocardiograms, under consideration of high-dimensional clinical and omics data.
Your profile:
In addition to the general requirements according to public services law, applicants must meet the recruitment requirements stipulated in § 57 of the Hochschulgesetz of Rhineland-Palatinate.
The ideal candidate has a master degree in Computer Science, Bioinformatics or Medical Informatics. Experience that relates to the topics of the project is a plus. Candidates must have excellent programming and mathematical skills, expert knowledge in machine learning and data mining, background knowledge in medicine/biology, be proficient in oral and written English, possess excellent communication skills, and be team- and result-oriented. Interaction with other researchers within curATime will be essential.
What we have to offer:
- Being part of a highly qualified team and a stimulating work environment
- We offer you comprehensive additional services:
- annual special payment
- participation in the additional pension scheme in the public sector via the VBL
- Jobticket, optional for the entire Rhine-Main area
- Extensive human resources development offer
- Flexible working time arrangements
The position is paid according to EG 13 TV-L and to be filled as soon as possible. The position is limited to a period of 3 years.
JGU is diverse and welcomes qualified applications from people with varied backgrounds.
We aim to increase the number of women in the field of research and teaching and therefore encourage female researchers to apply.
Candidates with severe disabilities and appropriate qualifications will be given priority.
Are you ready for a new challenge and interested in this varied and responsible position? Then submit your complete application [CV, transcripts, contact information of two or three referees, and a motivation letter in one PDF file) no later than 28th February, 2023 preferably via the „Apply now“ button.
For questions and further information please contact Prof. Dr. Stefan Kramer by e-mail: kramer@informatik.uni-mainz.de.
