Joint Lab for Artificial Intelligence - Hannover, Deutschland - Universität Osnabrück

Universität Osnabrück

Geprüftes Unternehmen

Hannover, Deutschland

vor 3 Wochen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

The Joint Lab for Artificial Intelligence & Data Science of the Leibniz Institute for Agricultural Engineering and Bioeconomy e. V. and Osnabrück University is establishing a Research Training Group.

The associated partners are Agrotech Valley Forum, German Research Center for Artificial Intelligence (DFKI) and Osnabrück University of Applied Sciences.

The core objective of the Joint Lab is to develop Artificial Intelligence (AI) & Data Science (DS) expertise, in particular for agricultural technology systems.

You are a passionate computer scientist or applied mathematician, intrinsically motivated to contribute your expertise to a societally highly-relevant research field?

For the Research Training Group, the Joint Lab for Artificial Intelligence & Data Science is looking for

3 Research Assistants (Postdoc) (M/F/d)

(Salary level E 14 TV-L, 100%):
All positions are for a period of 5 years, starting as soon as possible.

Your Duties:

Independently conducting scientific research on the intersection of (explainable) Artificial Intelligence and Data Science in Bioeconomic Systems
Publication of scientific results in internationally renowned journals and their presentation at national and international conferences
Acquisition of thirdparty funds and projects
Promotion of young talent, in particular supervision of bachelor's, master's and doctoral theses
Selfgovernance tasks of the Joint Lab

Required Qualifications:

A relevant doctorate with aboveaverage results as well as an aboveaverage academic degree (Master's or equivalent) in computer science, engineering, mathematics, environmental systems science, natural sciences, or related fields of study
Indepth expertise in at least one of the following relevant areas: Agricultural Robotics, Applied Multivariate Statistics, Data Aggregation, Data Driven Process Modeling, Deep Learning, Digital Twins, Domain Specific Hardware Architectures, Remote Sensing, (Explained) Artificial Intelligence, (Informed) Machine Learning, Navigation and Environment Recognition, Object Recognition, Recommender Systems, Sensor Data Fusion, Control Systems
Indepth knowledge of programming and according skills (e.g. in Python) as well as practical experience using ML and corresponding libraries (PyTorch, Tensorflow, NumPy, sklearn, etc.)

Additional Qualifications:

First experiences with versioning tools, such as Git, and unixbased systems, such as Linux
Flexibility, creativity and strong communication skills
High sense of responsibility, reliability, personal commitment and goaloriented and independent work as well as scientific ambitions
Very good English language skills (written and spoken), German language skills are a plus
Experience in supervising bachelor's and master's students
Experience in the acquisition of thirdparty funding
Experience in project coordination

We offer:

The opportunity to publish your papers in conference and journal publications
Project responsibility and cosupervision of doctoral students
A highly motivated and international team as part of the Research Training Group
Interdisciplinary support from UOS and ATB secured
Flexible work hours and excellent equipment
Broad selection of topics from the following areas, among others:
Artificial intelligence, explainable AI, computer vision, knowledge representation
Causal data analysis in complex agricultural systems
Intelligent recommender systems, multiparameter optimization
Datadriven process modeling and analysis of complex systems
Efficient/resourceconstrained sensor data acquisition and fusion
Domainspecific, resourceefficient, adaptive hardware architectures
Distributed systems, mobile systems with limited energy budget
Development of projectspecific infrastructure, digital twins
Informed Machine Learning (Physics-Informed Machine Learning)
Agricultural robots, control, navigation, environment detection, functional safety
Monitoring agroecosystems using multisensory earth observation data and AI

The Joint Lab connects the two locations Osnabrück and Potsdam, a willingness to travel is therefore required. The PhD students are supervised by a team of professors and scientists from Osnabrück and Potsdam.

The position is available on a full-time or part-time basis.

Osnabrück University is a family-friendly university and is committed to helping working/studying parents balance their family and working lives.

Osnabrück University seeks to guarantee equality of opportunity for women and men and strives to correct any gender imbalance in its schools and departments.