Offer Description
The Brandenburg University of Technology Cottbus–Senftenberg (BTU) brings together top-level research and knowledge transfer at an international standard, creating an interdisciplinary innovation network and an outstanding hub for science and technology. Together with its renowned partners, BTU forms the Lausitz Science Network – an alliance of research institutions working jointly to further develop the strengths of the Cottbus–Senftenberg science hub and increase its visibility. Through innovative research and new teaching and learning formats, BTU is shaping the future: it contributes scientific insights and practical solutions to addressing the major challenges and transformation processes of tomorrow. Across four profile areas – "Energy Transition and Decarbonization," "Health and Life Sciences," "Global Change and Transformation Processes," and "Artificial Intelligence and Sensor Technology" – it pools its strengths in teaching and research across institutes and faculties.
At its Cottbus and Senftenberg campuses, BTU offers its students an advanced education, individual support, and the opportunity to learn from and with one another with curiosity and openness. BTU stands for an inspiring atmosphere of learning and research within a dialogical, democratic community of all its members: the diversity of our faculty, staff, and students enables innovation and progress.
The Faculty of Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology invites applications for a
JUNIOR PROFESSORSHIP (W1, with tenure-track option to W3) Probabilistic Methods in Machine Learning
commencing on April 1st, 2027.
The Junior Professorship in "Probabilistic Methods in Machine Learning" is at the interface of applied mathematics, statistics, and computer science. It is dedicated to the development and the analysis of modern machine learning methods, with a focus on probabilistic modelling that enables, for example, to account for uncertainties when training neural networks, to capture complex and high-dimensional models and data, and to derive robust and interpretable predictions from them.
The professorship is embedded in a dynamic research environment in a rapidly changing region and seeks collaborations both within BTU and with non-university research institutions such as DLR or Fraunhofer institutes. The successful candidate is expected to engage in existing and new research initiatives, including those involving different faculties.
We are looking for:
A strong researcher with a forward-looking, internationally competitive profile in the field of probabilistic methods in machine learning. Possible research focus areas include stochastic simulation and approximation methods (for example, Markov Chain Monte Carlo, interacting particle systems, PINNs) or stochastic optimization (e. g., stochastic gradient methods for high-dimensional neural networks, reinforcement learning, variational inference). In addition to methods development and theoretical research on modern AI and ML methods, the successful candidate is expected to incorporate innovative approaches into their research that connect classical probabilistic models with modern deep learning architectures. Examples include Bayesian deep learning or the computationally efficient implementation of generative diffusion models for specific applications. A concrete connection to BTU's profile lines is desired.
In teaching, the junior professorship covers foundational and advanced topics in AI and data science within the MSc programs in Mathematical Data Science and Artificial Intelligence, while it also contributes to the undergraduate mathematics and computer science programs in the areas of probability theory and statistics, as well as to service teaching for other degree programs. This includes fostering early-career researchers through research-oriented teaching and supervision. Teaching will be carried out in both German and English. If the candidate does not yet have sufficient German language skills, they are expected to learn German soon, in order to be able to participate in the management of the institute, the faculty, and both university and non-university committees, as well as to teach in German-language bachelor's degree programs.
Profile
As the future junior professor, you can provide evidence of the following qualifications in accordance with § 47 (1) of the Brandenburg Higher Education Act (BbgHG):
- a completed university degree,
- teaching aptitude, and
- a special aptitude for academic work, generally evidenced by an outstanding doctoral degree.
Ideally, you also have experience in securing third-party funding and carrying out externally funded projects. Experience in DFG or EU projects is particularly welcome.
You are able to teach at all curricular levels, from bachelor's through doctoral studies, to supervise theses, and to support early-career researchers. Your knowledge and experience will also enable you to contribute to academic self-governance and to help shape the profile of the faculty.
We offer
- fair and transparent appointment negotiations,
- attractive working conditions in a city with a high quality of life, located in relative proximity to Berlin, Dresden, and Leipzig
- a dynamically developing research hub
- support with relocation to the vicinity of your workplace,
- comprehensive guidance through the Dual Career Service and family support
- an attractive salary with a negotiable appointment benefit.
Other duties result from the requirements set by § 44 BbgHG in conjunction with § 3 BbgHG.
The requirements and conditions for appointment are set out in §§ 47 and 48 BbgHG. According to § 47 Para. 2 BbgHG, the periods of full-time academic activity between the last examination performance of the doctorate and the application for a junior professorship may not exceed six years. These periods shall be extended to the extent of a reduction in working hours by at least one fifth of the regular working hours granted for the care or nursing of one or more children under the age of 18 or other relatives in need of care.
According to § 48 BbgHG, junior professors are appointed as temporary civil servants for a period of up to four years. If the interim evaluation is positive, the appointment is to be extended to a maximum of six years. After successful probation during the six-year junior professorship, there is the option, within the framework of the tenure track, to transfer a full professorship of grade W3 to the holder of the post after an appointment procedure has been carried out.
BTU is committed to equal opportunities and diversity and strives for a balanced gender ratio in all employee groups and gives priority to persons with severe disabilities or persons with equivalent qualifications.
Information on appointment management including the legal basis can be found at: https://www.b-tu.de/en/universitaet/karriere-engagement/career/professional-appointment-management
Please send your application with proof of qualifications, a tabular presentation of your professional career, a list of publications including the 3 most important ones, proof of pedagogical aptitude as well as a research and teaching concept for the advertised professorship by e-mail - mentioning the Reference-No: 123/26 - in a summarised PDF file (max. 7 MB) until [contact details available in the full listing] to:
E-Mail: [contact details available in the full listing]
Dekan der Fakultät MINT - Mathematik, Informatik, Physik, Elektro-und Informationstechnik,
Postal Address: BTU Cottbus-Senftenberg, Postfach 101344, 03013 Cottbus
When sending your application by unencrypted e-mail, please be aware of the risks regarding the confidentiality and integrity of your application content and please also note the data protection information on the BTU website.
For further information please contact Prof. Dr. Carsten Hartmann, Tel. +49 (0)355 / 69 4150, email: [contact details available in the full listing].
