The DMIR Research Group at the University of Würzburg offers a habilitation position for a postdoctoral researcher in the area of machine learning for temporal data.
DMIR Research Group, Computer Science Institute, University of Würzburg
We are situated at the Hubland Campus (South), Julius-Maximilians-University Würzburg, Germany.
The DMIR Research Group is a highly interdisciplinary group of researchers led by Prof. Andreas Hotho. We are active in machine learning and data science research with multiple applications domains like text analysis, environmental sensing and user analysis, recommender systems and anomaly detection (see https://dmir.org for details). In all of these areas, we deal with temporally variable data, thus necessitating the application, development and research of methods in the area of time series analysis. We are especially interested in combining the analysis of temporal data with formally represented and existing knowledge.
The position is a typical postdoc position for qualification with a maximum duration of 6 years. The position is not tied to a specific project. Research should be related to machine learning for time series with application in one of our existing domains. The possibility to do a habilitation and to head your own small research group in one of the application areas is given. The position is part of upcoming computer science chair X.
For your research, you will have access to a large cluster currently consisting of about 30 GPUs in 7 larger and some smaller compute nodes (with about the same amount of additional resources currently being procured). This will enable you to quickly develop and test new models even with large amounts of training data. We are extending this cluster into the direction of learning on large data, planning to have approximately 1PB of storage soon.
We are looking for a highly motivated postdoctoral researcher with an excellent PhD and strong experience in machine learning and/or data science. The core tasks associated with this position are:
◦ Pursue your personal research interests in a group of highly capable PhD students
◦ Work on projects with group members to gather experience in areas closely connected to your own research
◦ Publish on top tier venues in machine learning, data mining and data science
◦ Write proposals for new project grants
◦ Work towards advancing your academic career
◦ Receive guidance on the way to your habilitation
• Group Leadership
◦ Form your own group within the new chair guided by the chair holder
◦ Guide group members on their way towards their PhD thesis
◦ Provide your experience to PhD students writing their first papers
◦ Teach and assist courses in the areas related to your research, e.g. data mining
◦ Supervise bachelor and master theses
The ideal candidate has an excellent PhD in Machine Learning, Data Science, Data Mining or related areas with the intention to stay at the University and do research.
Core requirements are the ability of approaching research problems in a systematic way, working in a multidisciplinary team environment, exceptional problem solving skills and high creativity.
The following aspects are important factors:
• Ability to independently research complex topics
• Experience in various fields of machine learning, data mining, data science and related areas
• Interest and experience in the area of temporal data analysis
• Well-founded knowledge about neural networks and/or big data
• Willingness to share expertise and learn from others
• A strong publication record
• Advanced to strong oral and written English skills. Knowledge of German is a strong plus
The position is a limited-term contract from the earliest possible date with the goal of a successful habilitation. The maximum runtime is 6 years after the Ph.D. degree with salary based on TV-L.
There is the typical teaching load associated with this position. Please note that we will support you in the acquisition of projects and/or third-party funding.
The University aims to increase the proportion of female employees, therefore applications from qualified women are particularly welcome. Preference will be given to people with disabilities in the case of otherwise equal aptitude. The position can be filled part-time as well.
Please send your application (letter of motivation, curriculum vitae, academic records including one paper that you regard as especially noteworthy) at your earliest convenience, but no later than February 28th, 2019, to Prof. Dr. Andreas Hotho (email@example.com). You are welcome to contact us on the same address for additional details.