Profile

I live in Reading in a cozy studio flat with a wonderful view to the garden and neighbouring to good friends with their cat I occasionally babysit. I also use their freezer and tumbledrier on times as my place is too small. I’m originally from Germany, but also haved lived in Austria and Italy for a short while during my undergrad studies where I met lots of lovely friends and could explore the local culture.

I came first to the UK via the ERASMUS programme during my Master’s degree, got hooked and came back to work and have lived here ever since.

I like the campus life of the University of Reading and am a member of the Senior Common Room (a staff social club), where I also have a role as Junior Wine Steward. Here, I organise wine tastings for the members, help running out campus wine shop and providing wines and services for events. It’s always good fun and I have learnt a lot about the world of wine. At our events I also enjoy meeting people from other schools and departments and have made some research connections.

The pictures below show some excerpts of my experiments in Microbiology.

Agar plates streaked with bacteria. At the right the yellow culture is Staphylococcus Aureus, to the left the white culture is Pseudomonas Aeruginosa. I pick one colony (one dot) and mix it into liquid growth medium and grow it for another 24 h before I can use it for experiments.

Screenshot of a 24h bacterial growth reading of a 96 well-plate. The plate has in total 4 different bacterial strains and 4 different molecules at a fixed concentration. I want to see which molecules stop or reduce bacterial growth and which ones don’t have an effect at all. The fields with the flat lines either contain the controls, no bacteria at all or molecules that have stopped the bacterial growth. E.g. A1, A2, A3 contain all the same bacteria with the same molecule and are called a technical repeat. I can see from the small picture that this molecule killed all the bacteria in the wells. However, I need to analyse the data further in Microsoft Excel to produce meaningful graphs.

Raw data of the 96-well data converted into an average graph in Excel. Comparing different molecules (G2.5, G3, G4.5 and G5) with the controls (LB, MeOH). G3 and G5 show complete stop of the growth of Bacillus subtilis, whereas G2.5 and G4.5 are similar to the control.

Usually in the morning, I have allocated the first 0.5-1 h to work on emails and plan my day/week whilst having coffee and breakfast in my office. I plan details of experimental work that I need to on that day or in the week if it is a multiple-day experiment and also what I will do with the results in terms of analysis and visualisation. At least once a week I also spend some time searching for the latest research literature in my field to keep me updated.

Then I spend some time in the lab for my experimental work, at the moment in a microbiology lab. Typical tasks here involve streaking bacterial solutions on agar plates to grow solid, immobile colonies, make liquid cultures by mixing a colony into liquid growth medium, prepare solutions of my sample (the taxi molecule), pipette solution and bacteria in plates with 96 wells and measure for 24 hours how the bacteria grown with a machine that is connected to a computer. I want to know if the molecule I am working with is killing the different types of bacteria and could therefore be used to fight bacterial infections.

Lunch I spend normally with a friend and colleague of mine, and we discuss matters of the day, teaching we do together, results and also our personal life.

The afternoon I can spend with analysing my results, preparing for meetings with my supervisors or other colleagues catch up on more paperwork or do more experiments.

After work I either go indoor climbing with colleagues at the local climbing centre or have drinks or a meal in our campus bar.