Dr. Maik Wolfram-Schauerte

Postdoc - AI & Data Science Fellowship Program
Integrative Transcriptomics
Interfaculty Institute for Bioinformatics and Medical Informatics (IBMI)
Sand 14
72076 Tübingen
+49 07071 - 29-70464

Research topics

Transcriptomics machine learning models
Development of hybrid transcriptomics machine learning models for drug discovery. In order to approach a holistic transcriptome model, both unsupervised and supervised learning are applied to integrate transcriptomics data. This project is part of the AI & Data Science Fellowship Program (https://uni-tuebingen.de/en/237054) – a collaboration between Tübingen University and Boehringer Ingelheim – aiming to develop cutting-edge machine learning models with implications for pharmaceutical research.

 


Short Biography

Education & Selected Work Experience
Since 2024      Postdoctoral researcher at Integrative Transcriptomics group within AI & Data Science Fellowship Program (https://uni-tuebingen.de/en/237054)
2021 – 2024    Doctoral research in Bacterial & Phage Epitranscriptomics at Max Planck Institute for Terrestrial Microbiology, Marburg
2018 – 2021    Master of Science in Biochemistry at Heidelberg University | Master’s thesis in Bacterial Epitranscriptomics at Max-Planck-Institute for Terrestrial Microbiology, Marburg
2015 – 2018    Bachelor of Science in Molecular Biotechnology at Heidelberg University | Major subject: drug discovery
Scholar- & Fellowships
2022 – 2024    Doctoral scholarship | Studienstiftung des deutschen Volkes e.V.
Since 2021      Add-On Fellowship for Interdisciplinary Life Sciences | Joachim Herz Foundation
2019                ERASMUS scholarship for Master’s internship on enzyme engineering
2017 – 2021    Scholarship | Studienstiftung des deutschen Volkes e.V.
See also LinkedIn


Teaching Assistance

Winter 24/25 Seminar "Bioinformatics and Machine Learning"

Supervision & Students

Student Assistant, B.Sc. Thomas Vogel, within Project "Transcriptomics machine learning models"


Publications

For entire publication record take a look at Google scholar or ORCID.