top of page

Interested in joining the team?

We have a range of interesting topic available ranging from very chemistry focused to very programming focused. For detailed information contact Dennis and arrange a meeting.

Topics include classic computational investigations of chemical reactions to create insights, development of machine learning approaches to develop better chemical reactions, development and application of new analysis methods, and improving chemistry education through the use of 3D models.

If you are interested in organic chemistry, computers, programming, teaching, or application of bioorthogonal chemistry, you have found the right team!

Bioorthogonal Chemistry

Bioorthogonal chemistry, reactions that can be performed in biological media, have great potential to revolutionize medical technologies such as cancer therapy. To enable such applications the reactions have to be highly efficient. Computational chemistry allows us to understand and optimize these reactions that are used in experimental work in the Mikula lab.


Representative research work: 

Energy Decomposition Methods

Energy decomposition analysis methods allow us to interpret computational results in a way that creates a very intuitive way of looking at chemical interactions. In our research we employ and develop such methods to gain in-depth understanding of organic reactions. 


Representative research work:

Genetic Algorithms

To improve bioorthogonal reactions we are working on so-called "genetic algorithms" that allow us to optimize reaction partners in software, before they are evaluated experimentally. Genetic algorithms rely on randomly generating "mutations" of chemical structure and evaluating them for fitness. The best candidates are then moved forward, similar to natural selection.

3D Models in Chemistry Education

In the group we are developing 3D models for chemistry education based on 3Dmol.js.

See also:

bottom of page