W 155/2023 Research Assistant bei Universität Rostock

Universität Rostock

Job Advertisement W 155/2023

The University of Rostock offers a diverse, varied and demanding job in a tradition-conscious, yet innovative, modern and family-friendly university in a lively city by the sea.

At the Faculty of Computer Science and Electrical Engineering, Institute for Visual and Analytic Computing, Chair of Intelligent Data Analytics, subject to budgetary provisions, we are filling the following position within the framework of a newly founded, dynamic Machine Learning Group at the earliest possible date on a temporary basis for a period of three years with the option of transferring additional, higher-ranking activities up to EG 14:

Research Assistant (PhD Student oder PostDoc) (m/f/d)
EG 13 TV-L, full-time employment, 40 hours/week, limited, qualification position

The Becker Lab represents the Chair of Intelligent Data Analytics at the Institute of Visual and Analytic Computing and the Faculty of Computer Science and Electrical Engineering. You will be part of a research group for knowledge-based machine learning and applications in biomedicine, environmental sciences and human behaviour. The position offers the perfect conditions to develop your own research programme, with access to an international network such as Stanford University, UC San Diego and UNC Chapel Hill. This gives you direct access and collaborations with experts in machine learning, (bio)medicine and marine ecology worldwide. You will have the unique opportunity to help build and shape a dynamic, collaborative and team-oriented group that aims to solve highly relevant, practical problems using state-of-the-art machine learning in a trans-regional and international context. The existing contacts as well as the recently acquired BMBF research group also offer perfect conditions for a doctorate or, given the appropriate qualifications, the chance to work as a postdoc in a leading position and to build up your own research profile.

We are particularly interested in methods for understanding the underlying processes of complex systems, the integration of domain knowledge into machine learning methods for accurate modelling, and the human handling of existing knowledge. We welcome your expertise in many areas and approaches, such as multimodal and/or multi-task models, deep learning, Bayesian modelling and exceptional model mining, through to explainable artificial intelligence, fairness and human-computer interaction.

Our group is committed to translating research into actionable insights and applications with real-world impact and scalability. This is an excellent environment for candidates who not only want to conduct groundbreaking and creative research, but are also interested in implementing results in an industrial and entrepreneurial way.

We prioritise a friendly, supportive, team-oriented and inclusive working environment with a highly motivated team of colleagues. Diversity across all dimensions is a central principle for our working group and an important contribution to our innovative research.

Tasks and Responsibilities

• research in the fields of Data Science, Machine Learning and Artificial Intelligence in application scenarios such as (bio-)medicine and environmental change with the goal of scientific qualification with the aim of scientific qualification (doctorate or habilitation)
• develop and apply methods ranging from multimodal learning, deep learning, Bayesian modeling, and exceptional model mining to explainable artificial intelligence, fairness, and human-computer interaction
• scientific teaching in the amount of approx. 4 semester periods per week in the form of integrated courses, projects, seminars and internships in the field of computer science, whereby the research-based transfer of specialist knowledge and skills to students is central and they are instructed to work scientifically on their own due to the scientific nature of teaching
• collaborate with international partners at universities, including Stanford, UC San Diego, or UNC Chapel Hill.
• publish scientific papers in (inter-)nationally renowned conferences and journals
• supervising bachelor, master and doctoral students
• organize and conduct scientific events

Requirements

• completed university degree (diploma, master's degree or comparable degree) in the fields of computer science, mathematics, physics, computational biology, medical informatics or a comparable field with at least good results
• in the case of employment with the aim of habilitation, a doctorate in the above-mentioned subject area with at least good results (cum laude) must also be presented
• strong analytical thinking skills
• very good knowledge in the development and application of statistical and/or machine learning methods as well as very good programming skills, preferabl