Within a project, students will learn how to tackle a research project. They will work together with Phd-students and postdoctoral researchers and develop detailed knowledge of a topic of current research.
Here, initial MATLAB simulations are supposed to accompany the project work. Furthermore, students will learn how to read scientific texts effectively and to report research findings in writing and in seminar presentations.
In a Bachelor/Master thesis, students will get insight into a topic of current research. They will learn how to use MATLAB for implementing algorithms and carrying out simulations. Real data may be available as well, depending on the chosen topic.
Students are encouraged to realise their own ideas within the project. Generally, the projects can be adapted to the student's interest. The following list provides a selection of student projects which are currently offered by the Bioinspired Communication Systems Lab:
Current available projects:
- Higher-order integration schemes for jump-diffusion models of biomolecular reaction networks
- Scheduling algorithms in wireless networking using machine learning
- Machine Learning for Image Analysis and Cell Segmentation in Biological Research
- Scalable Generative Models for Dynamic Network Data
- Traffic modelling using machine learning
- Machine learning for adaptive video streaming
- Learning non-Markovian multi-component temporal processes from biological high-throughput data
- Object Recognition Techniques for Bacterial Swarming
- Machine learning of memory functions of marginal stochastic processes
- Comparison of machine learning methods for the classification of high-throughput gene expression data
- Design and cloning of a system to visualize transcription in real time based on FRET
- Design and cloning of a system to visualize transcription in real time based on protein complementation
- Implementation of post-transcriptional regulated cell-free circuits into microfluidic chemostat
- Measurements of genetic logic gates in yeast with microfluidic chips
- Investigation of the transcriptional level of ribosomal genes in yeast with microfluidic chips
- Optimization of transcription site measurements in mammalian cells
- Variational Inference for Spot Tracking in Fluorescence Microscopy