Primary Goals:

1. Literature Review of timing/oscillation/synchronization methods that use (stochastic) chemical reaction networks in simulation and experiments.
2. Implement and compare different proposals (focusing on oscillators) from literature using Python?
   How do we measure how well they work (metrics)?
   How are all the options different from one another?
   Do they work using deterministic and stochastic simulation?
3. Think about potential changes to the existing oscillator methods based on the use cases in MC networks
4. Implement at least one option of the oscillators for a simple toy example CRN algorithm to showcase how it could work

Primary Goals:

1. Review and understand current CRN implementations in Python
2. Review and summarize candidate optimization methods (Bayesian optimization, random forests, neural networks, ...)
3. Implement and evaluate different proposals from literature using Python
4. Optimize parameters and structure of a CRN for successive interference cancellation
5. Evaluate hyper-parameters, utilize stochastic simulation methods, improving the efficiency of the algorithms

The Wireless Sensor Networks lab offers the opportunity to develop software solutions for the wireless sensor networking system, targeting innovative applications. For the next semester, a position is available to assist the participants in learning the programming environment and during the project development phase. The lab is planned to be held on-site every Tuesday 15:00 to 17:00.

Prerequisites