Reconstructing clonal evolution in blood cancer

The Challenge
Cancers, including leukemias and lymphomas, do not present homogeneous cell populations, but often have complex subclonal structures. Moreover, upon therapy those subclonal structures can undergo significant shifts leading to a more aggressive and therapy-resistant tumor. Here, we want to develop novel ways to reconstruct clonal evolution in non-solid tumors using single cell transcriptomes.
To this end, we will generate longitudinal single cell data from xenografted AML mice, which will include transcriptomes and barcodes to determine cellular identity. This is an unprecedented opportunity to characterize the short term evolutionary changes in the trancriptome.
For further information please see and Hellmann lab
Your responsibilities:
  • Analysis of genome and transcriptome data, data visualization; integration of genomic and transcriptomic data.
  • Directing the generation of cutting edge single cell data tailored for this project.
  • Application and extension of evolutionary and population genetic models to (single-cell) transcriptome data.
  • Develop an R-package.
Your profile:
  • Master/Diploma degree in Statistics, Biostatistics, Biology or related areas. Very good knowledge of statistics.
  • Interest in Evolutionary Biology.
  • Strong programming skills (R, Python or Java  etc.)
  • Proficiency in written and spoken English
Your opportunities:
  • We offer a highly interdisciplinary environment for state-of-the-art genomic technologies and computational and evolutionary data analysis within the group and within the Collaborative Research Centre (SFB) 1243.
  • You will be part of the Integrated Research Training Group (IRTG), a structured graduate program committed to providing an excellent all-round graduate education.
Online applications are now being accepted until February 21, 2016. Please apply solely via Choose A15 as priority.
The position should start as soon as possible and is for a period of 3-4 years. The LMU is an equal opportunity employer. Preference will be given to suitably qualified female applicants or handicapped people, all other considerations being equal.

How to apply:

Contact detail

How to apply:
Send application to
Dr. Ines Hellmann, Anthropology and Human Genomics, Department Biology II Ludwig Maximilians University Munich Grosshaderner Str. 2 D-82152 Martinsried E-mail:

Job profile

Working hours
Contract duration
Type of job
PhD Project
Work experience
job experience is not required
Germany (Bayern)
Working place
82152 Planegg - Martinsried
Area of expertise
Biology & Life Sciences

About Enard lab, LMU Munich

We are based in the faculty of biology and work on functional genomic approaches to understand human evolution and disease.

More about Enard lab, LMU Munich

Related jobs

Get jobs on a daily basis for free