Diplom und Abschlussarbeiten

Thema: Zucht, Untersuchung und Vergleich verschiedener Pilzstämme

Ants recognize their nestmates by “smelling” the waxy hydrocarbons on each other’s bodies—but ozone pollution can chemically alter these cues and confuse entire colonies. This project dives into the chemosensory mechanisms behind this phenomenon: How do antennal sensilla detect oxidized versus intact hydrocarbons? You will combine behavioral assays and chemical analysis to unravel how environmental change reshapes insect communication.

THESIS OBJECTIVES As part of the BMLEH (FNR)-funded project LCR-PILZE, the potential of anaerobic fungi to improve methane yield during biogas production is being investigated in a pilot-scale biogas plant. The main hypothesis to be tested is if biological pre-treatment with anaerobic fungi accelerates degradation of lignocellulose-rich agricultural fermentation residues resulting in a more efficient biogas production. For this, the biogas production of 4 selected anaerobic fungi strains is determined using anaerobic batch reactors. TASKS Determination of biomethane potential (BMP) of anaerobic fungi in batch tests Assessment of lignocellulose degradation efficiency Comparison of the effects of biological pre-treatment of lignocellulosic residues with chemical and physical pre-treatment methods Hands-on work at the biogas pilot plant in Dürnast REQUIREMENTS Enrolled Bachelor’s student in Biology, Molecular Biotechnology, Bioprocess Engineering or a related field Good theoretical background in microbiology Experience with microbiological laboratory methods, ideally anaerobic microbiology Interest in sustainable biogas production processes WHAT WE OFFER Opportunity to contribute to an interdisciplinary and sustainable research project Training in methods of (anaerobic) microbiology and chemical analytics Insights into technical scale biogas plant Interested? Send an e-mail including a letter of motivation and short CV (incl. relevant expertise/internships etc.) to: cristina.gonzalezrivero@lfl.bayern.de

Du begeisterst dich dafür, modernste Informationstechnologien einzusetzen, um die Energie- und Klimakrise zu lösen, und möchtest in einem dynamischen Forschungsumfeld arbeiten? Dann lass uns gemeinsam die Energiesysteme der Zukunft gestalten!

The Chair of Robotics, Artificial Intelligence, and Real-Time Systems offers a Master’s thesis focusing on adaptive cooperative perception for ETSI-based Vehicle-to-Infrastructure systems using covariance-aware movement clustering and track-to-track fusion. The thesis investigates how object information from CAM and CPM messages, including covariances, velocities, and object parameters, can improve multi-agent object association and global tracking in urban traffic scenarios.

Simulation and Algorithm Development for a novel Laser-based Eye-Tracking Sensor, embedded in an industry-led EU project. Keywords: Eye-Tracking, Sensors, Signal Processing, Machine Learning, Computer Vision

The goal of this thesis is to develop an method for generating edge cases for temporal-logic described traffic rules to assist in their validation and refinement.

Das Team von Prof. Stephen Schrettl an der Technischen Universität München (TUM, Campus Weihenstephan) bietet im Rahmen des durch die Bayerische Transformations- und Forschungsstiftung geförderten Verbundprojekts BayWater eine Masterarbeit in Kooperation mit der Infineon Technologies AG am Standort Regensburg an.

Thema: Untersuchung industrieller Nebenströme bei Pilzzuchtsubraten