Postdoc in Computer Science in Georg-August-Universität Göttingen – Germany

Summary

The Georg-August-Universität Göttingen is seeking a Data Scientist / Postdoc for its KIForst Competence Center. This full-time position involves working at the intersection of machine learning, deep learning, data science, and forest sciences. The successful candidate will help establish a faculty-wide infrastructure for AI applications in forest sciences, focusing on model explainability and trustworthy AI. Responsibilities include translating research questions into AI approaches, developing solutions in Python, supporting research groups, and delivering teaching activities. The role also offers opportunities for academic development, including publications and third-party funding proposals. Applicants should have a Master's and PhD in a relevant quantitative discipline, strong Python skills, and initial experience in teaching or consulting. The application deadline is October 12, 2026.

Key Facts

Department	KIForst Competence Center
Position Type	Postdoc
Discipline	Computer science
Research Area	Machine learning, deep learning, data science, computer vision, explainable AI, trustworthy AI, forest sciences
Degree Required	A successfully completed university degree at Master’s level or equivalent and a completed PhD in computer science, data science, computational science or a comparable quantitative discipline.
Experience	Demonstrated scientific expertise in machine learning and deep learning. Knowledge of explainable AI (XAI), uncertainty analysis and model validation. Strong Python skills, experience with deep learning frameworks such as PyTorch, and tools for processing complex and/or spatial data. Initial experience in teaching, workshop facilitation, supervision or scientific consulting.
Funding	Not funded by a EU programme
Contract Duration	To be defined
Language	Very good written and spoken English; German language skills or a willingness to acquire them in the near future.
Deadline	2026-10-12
Employer Contact	https://uni-goettingen.de/en/710650.html

About the Project

The KIForst Competence Center aims to establish a faculty-wide infrastructure that integrates expertise in artificial intelligence with applications in forest sciences. The project focuses on developing and implementing AI solutions, particularly in machine learning, deep learning, and computer vision, with a strong emphasis on model explainability and trustworthy AI. The goal is to enable forest science researchers to apply AI methods effectively and soundly, providing methodological support, consulting, and training. The project also involves contributing to third-party funding proposals and scientific publications.

Key Responsibilities

• Translate research questions into appropriate data science and AI approaches and support selected projects from problem definition through to validated implementation.
• Develop solutions using machine learning, deep learning and computer vision, and independently implement key components in Python.
• Develop explainable AI approaches that enable forestry experts to understand and build confidence in model decisions.
• Support research groups in selecting methods, study design, data preparation, modelling and computing infrastructure, and contribute to gradually establishing an an AI consulting service.
• Design and deliver teaching activities, workshops, professional training courses and reusable learning materials for different target groups.
• Contribute to third-party funding proposals and scientific publications.

Required Skills

• Successfully completed university degree at Master’s level or equivalent and a completed PhD in computer science, data science, computational science or a comparable quantitative discipline.
• Demonstrated scientific expertise in machine learning and deep learning.
• Knowledge of explainable AI (XAI), uncertainty analysis and model validation.
• Strong Python skills, experience with deep learning frameworks such as PyTorch, and tools for processing complex and/or spatial data.
• Initial experience in teaching, workshop facilitation, supervision or scientific consulting.
• Very good written and spoken English.
• German language skills or a willingness to acquire them in the near future.
• Ability to communicate complex methods clearly.
• Ability to familiarise yourself with research questions outside your own discipline—including forest science—and collaborate effectively with different research groups.
• Knowledge of HPC or cloud computing (desirable).
• Practical experience with computer vision (desirable).
• Experience with databases, research data management, GIS or geospatial data processing (desirable).

Who Should Apply

This position is suitable for a methodologically strong and communicative individual with a completed PhD in computer science, data science, computational science, or a comparable quantitative discipline. Candidates close to completing their PhD are also encouraged to apply. The ideal applicant will have demonstrated scientific expertise in machine learning and deep learning, knowledge of explainable AI, strong Python skills, and initial experience in teaching or consulting. An interest in forest science research questions and the ability to collaborate effectively across disciplines are essential.

Benefits

• Opportunity to play an active role in shaping and establishing a new faculty-wide competence center.
• Varied scientific work addressing a broad range of research questions in forest sciences.
• Scope to develop your own methodological focus and pursue publications and third-party funding initiatives, provided that these emerge from KIForst activities and pilot projects.
• Interdisciplinary collaboration with research groups across the Faculty as well as partners from data science.
• Access to high-performance scientific computing infrastructure and an interdisciplinary research environment across the Göttingen Campus.
• Flexible working arrangements and additional opportunities for mobile working in accordance with applicable regulations.

About the Employer

The Georg-August-Universität Göttingen is establishing the KIForst Competence Center, a faculty-wide infrastructure that brings together expertise in artificial intelligence and its applications in forest sciences. It offers an interdisciplinary research environment across the Göttingen Campus and access to high-performance scientific computing infrastructure.

Frequently Asked Questions

What is the primary focus of the KIForst Competence Center?

The KIForst Competence Center focuses on establishing a faculty-wide infrastructure that combines expertise in artificial intelligence with its applications in forest sciences.

What are the main technical skills required for this position?

Required technical skills include demonstrated scientific expertise in machine learning and deep learning, knowledge of explainable AI (XAI), uncertainty analysis and model validation, strong Python skills, and experience with deep learning frameworks such as PyTorch.

Are German language skills mandatory for this role?

Very good written and spoken English is required. German language skills are desirable, or a willingness to acquire them in the near future.

What opportunities are available for academic development?

Part of the working hours is allocated for academic development, allowing the Postdoc to develop their own academic profile, produce publications, and prepare applications for third-party funding, with support from academic mentors.

Is this job funded by an EU Research Framework Programme?

No, this job is not funded by an EU Research Framework Programme.

What is the application deadline for this position?

The application deadline is October 12, 2026, at 23:00 (UTC).