MLO Lab

Machine Learning in Oncology

Who we are

Our mission is the application and collaboration driven development of interpretable and statistically sound machine learning methods for understanding disease heterogeneity. As part of the DKTK/DKFZ and hosted by Frankfurt University we thrive to use machine learning for accelerating progress in personalised oncology.

We build on probabilistic machine learning to address computational challenges in three areas: translational single-cell genomics, computational proteomics and the integration of multi-omics data.

Team

Researchers

Avatar

Florian Buettner

Professor for Bioinformatics in Oncology

Machine Learning (ML), Precision Oncology, Multi-omics data integration

Avatar

Sebastian Gruber

Ph.D. Candidate

Calibration, Out-of-domain Generalization, Hyperparameter Optimization

Avatar

Arber Qoku

Ph.D. Candidate

Probabilistic Modelling, Multi-omics Data Integration, Tensor Factorisation

Students

Avatar

Xiaoyan Feng

Student

Encoding Pathway Gene Sets with Sparse Priors for Inferring Explainable Latent Variables

Avatar

Tim-Oliver Ewald

Student

Simulation and Evaluation of Distribution Shifts on Tumor Images

Avatar

Tim Diedrich

Student

Hidden Functional Activity in JOANA

Guest Researchers

Avatar

Andreas Kopf

Guest Scientist

Machine Learning (ML), Deep Learning, Probabilistic Modeling

Teaching

In the summer term 2021 we offered Introduction to AI, have a look at the Vorlesungsvereichnis here.

In the winter term 2021/2022 we offer a seminar on AI in Medicine. Please contact me directly if you are interested/have any questions. Further information will be provided via moodle: https://moodle.studiumdigitale.uni-frankfurt.de/moodle/course/view.php?id=2046. The course is now open for self-registration - please only register in moodle if you are assigned to this seminar.

Open Positions

We are hiring! We have open positions for a PhD student and a postdoc and looking forward to your application here and here!

We are always interested in talented MSc and BSc students interested in machine learning for genomics data and offer topics for MSc theses and BSc theses. If you’re interested, just contact us and we’ll have an informal chat!

Contact