Die Hochschule für nachhaltige Entwicklung Eberswalde (HNEE) ist mit ihrer ganzheitlichen nachhaltigen Ausrichtung, ihrem einzigartigen und an zukunftsrelevanten Themen ausgerichteten Studienangebot und als starke Institution im Bereich der Nachhaltigkeitsforschung Impulsgeberin für nachhaltige Entwicklung. Rund 2.300 Studierende aus etwa 60 Nationen studieren und mehr als 400 Beschäftigte lehren, forschen und arbeiten an der modernen Campushochschule. Die Transformation hin zu einer nachhaltigen Gesellschaft durch die Entwicklung tragfähiger Modelllösungen voranzutreiben und die Studierenden mit den erforderlichen Gestaltungskompetenzen auszustatten, das ist die Mission der HNEE.
An einem der zukünftigen Departments ist zum nächstmöglichen Zeitpunkt folgende W2 Professur unbefristet zu besetzen.
Explorative Datenanalyse in den Holzwissenschaften
unbefristet besetzen.
Around 2,300 students from about 60 nations study and more than 400 employees teach, research and work at the modern university. The mission of the HNEE is to lead the transformation towards a sustainable society by developing viable model solutions and equipping students with the necessary skills to shape the future.
The following W2 professorship (100%) is to be filled on a permanent basis at one of the future departments as soon as possible.
Data Mining in Wood Sciences
What to expect
The professorship is embedded in the university's profile of forestry and wood science expertise. With the professorship, you will form a bridge between accessible data sets, in all their diversity and variability but also with special reference to data sets generated at HNEE, as well as the university's big data structures and thereby promote the use of these for sustainable wood processing value creation. Through data mining, you facilitate the reflection of a complex reality from which, for example, specific and individualized questions about the raw material wood in structure, processing and utilization can be modeled and resolved, also in the context of provenance. They thus support structural and material performance prognoses and application-optimized processes in wood science and engineering.
Based on mathematical-statistical principles, you will develop AI and other digital models of material behavior and material production, thus enabling knowledge to be gained in the fields of production technology and materials science. As a renowned scientist in the fields of mathematics/statistics, computer science, machine learning or with a background in materials science, especially wood science, which shows a familiarity with the various methods of machine learning, you will support the Center for Data Science at HNEE with your expertise and promote a cross-institutional database-related research project.
You will give courses in German and English in mathematics and statistics in classical engineering disciplines, as well as in areas of mathematical approaches in raw materials management and in AI applications with a focus on machine learning and deep learning.
As a potential new colleague, you will represent your field in its full spectrum, implement innovative ideas for application-oriented research and development tasks and demonstrate the alignment of research and education. Your approach and mindset are characterized by an interdisciplinary perspective. An active engagement with current trends in practice, research and teaching is a self-evident part of your work.
The regular teaching load is 18 SWS.
Formal hiring requirements are according to § 43 (1) sentence 1 nos. 1-3 and 4 letter b and sentence 2:
Completed university degree, special aptitude for academic work, usually proven by the quality of a doctorate, as well as pedagogical aptitude and special achievements in the application or development of scientific knowledge and methods in at least three years of professional practice, of which at least two years must have been spent outside the university sector or over a period of at least three years the majority of the professional activity must have been carried out in cooperation between the university and non-university professional practice.
In addition, identification with the university's commitment to sustainability is a prerequisite. The university is currently revising its internal structure. We therefore expect you to be willing to play a constructive role in this exciting and challenging project.
Your advantages at the HNEE
The HNEE offers you a modern, family-friendly workplace in a green environment with very good public transport connections. The university offers subsidies for the VBB job ticket, flexible working hours and the possibility of mobile working. Furthermore, we support our employees through active health management. The HNEE promotes the personal development of university staff through an extensive internal and external training and further education programme.
We value the diversity of our members and want to use different perspectives as potential to find creative and innovative solutions for future issues together. We therefore look forward to receiving your application - regardless of your gender, nationality, ethnic and social origin, religion or belief, sexual orientation and identity, disability and age. We would also like to recruit more applicants with gender and diversity skills.
As female professors are underrepresented at the HNEE, we would like to encourage female scientists in particular to apply for this call.
We also want to explicitly invite severely disabled people and those with equal rights to apply and will give them preferential consideration if they are equally qualified.
Please send your application with the usual documents (cover letter, curriculum vitae showing academic career, list of publications and teaching courses, academic certificates, proof of teaching experience, third-party funding, gender-sensitive teaching and research concept) by 17. March 2025 directly via the online
Questions regarding content: Prof. Dr. Peter Neumeister ()
Questions about the procedure
Questions about equality
In the case of appointment to a civil servant position, a legally prescribed standard enquiry is initiated to check compliance with the constitution (see ).
If you apply, we will collect and process your personal data in accordance with Art. 5 and 6 of the EU-DSGVO only for the purpose of processing your application and for purposes arising from possible future employment at HNEE. After six months, your data will be deleted. You can find more information here
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