Schulz Lab
Jobs
Open Positions
You are interested to work at our institute? Great! Then have a look at the offers below. We are always looking for talented individuals with good programming skills and an interest in algorithms and machine learning in the context of the systems biology and genomics projects in our group. Join a highly motivated team with great working athmosphere at a prime location! Postdocs interested to work in the group directly contact Marcel Schulz with CV and list of references.
| Open Positions | Application deadline |
| Currently none |
Application procedure
We appreciate that you are interested to work with us. When you apply for a job please write an email to
sekretariat-schulzlab|uni-frankfurt.de
with a CV, including a list of publications, and at least two references that can be contacted.
We are generally interested in people with a quantitative background (Bioinformatics, Computer Science, Math) and are open to people who want to cross disciplines to increase their scientific skills.
Bachelor / Master thesis topics
We offer topics surrounding ongoing projects in the lab, which can serve as thesis for Bachelor/Master students topics. Get in contact with us if you are interested in joining us and we can schedule a meeting for discussion. Don't be afraid to ask!
Students from Bachelor or Master in Bioinformatics, Informatics, Statistics, Molecular Medicine and Biowissenschaften are eligible!
| Title | Degree | Year |
| Examples for previously completed theses | ||
| A refined mapping algorithm for single cell DNA methylation data | Bsc Bioinformatics | 2020 |
| An extended pipeline for analysis and validation of Split-ORFs | Msc Bioinformatics | 2021 |
| Assessing the power of transcription factor motif enrichment analysis using ChIP-seq and epigenomic data | Msc Bioinformatics | 2021 |
| Multi label classification methods for the prediction of lncRNA functions | Msc Informatics | 2021 |
| A machine learning approach for enhancer-gene prediction from single cell ATAC and RNA data | Msc Informatics | 2022 | Explaining regulatory DNA variation with interpretable convolutional neural networks | Msc Bioinformatics | 2022 |
| SeRP_HMM: Inferring Binding States from Selective Ribosome Profiling Data with a Hidden Markov Model | Bsc Bioinformatics | 2025 |