Master Thesis On Spatial Omics Data Analysis - Munich, Deutschland - Technische Universität München

Technische Universität München
Technische Universität München
Geprüftes Unternehmen
Munich, Deutschland

vor 1 Monat

Lena Wagner

Geschrieben von:

Lena Wagner

beBee Recruiter
Beschreibung

Duration: 6 months


Start Date:
As soon as possible.


Supervisors:
Johannes Wirth, M.Sc., PD Dr. Katja Steiger, Prof. Dr. Peter Schüffler


Background:

Intra-tumoral heterogeneity (ITH) is one of the major causes for unsuccessful treatments in human cancers.

The development of spatially-resolved transcriptomic (ST) methods facilitates the exploration of heterogeneity in tumor samples and gives the opportunity to better understand cancer biology and treatment responses.

In situ sequencing (ISS) uses an imaging-based approach to map single transcripts at subcellular resolution and characterize the transcriptional state of nearly all cells of a tissue section.

Currently, spatially-resolved transcriptomics represents one of the most promising biological methodologies and is expected to shape biological research in the coming decades.


Problem:


Goals:


  • Writing an opensource, Pythonbased toolbox to efficiently analyze large in situ sequencing spatial transcriptomic data using a high performance cluster.
  • Benchmarking different segmentation methods to ensure optimal cell segmentation.
  • Packaging the code and making it publishable.

What We Offer:


  • The opportunity to work in an interdisciplinary research team at the intersection of pathological, clinical, and molecular biological research.
  • Access to the highperformance computing cluster of the Leibniz-Rechenzentrum (LRZ).
  • Access to unique datasets of the stateoftheart in situ sequencing system 'Xenium in situ.'

Requirements:


  • B.Sc. in bioinformatics, computational biology, biology, or a related field.
  • Sound knowledge of Python or a comparable programming language.

Preferred Qualifications:


  • Familiarity with tools for the analysis of singlecell or spatial transcriptomics methods (Scanpy, spatialdata), Image analysis (Napari, QuPath, ImageJ), Bash scripting, Python packaging

Contact Information:


Supervisors:
Johannes Wirth, M.Sc., PD Dr. Katja Steiger, Prof. Dr. Peter Schüffler
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