[BBC] PhD Candidate Tumor Heterogeneity in Acute Myeloid Leukemia

[Erik van den Akker]

THE POSITION

We are looking for a highly motivated candidate for a PhD project in
Computational Oncology at the department of Biomedical Data Sciences. This
project focusses on modelling tumor heterogeneity and discerning drivers of
clonal evolution and therapy resistance by analyzing single-cell data on
material derived from patients with acute myeloid leukemia.


IN SHORT

• You will work on integrative computational methods to discern,
characterize and trace different clonal lines present within tumors

• You will work in a multi-disciplinary environment ranging from data
science to translational oncology within the recently established Leiden
Center for Computational Oncology

• You will disseminate your work by writing scientific manuscripts and
presenting your research at international conferences. The combination of
this work will lead to a PhD title


WHAT YOU WILL DO

Acute myeloid leukemia (AML) is a cancer of the myeloid immune lineage and
represents about 1.2% of all new cancer cases. AML typically affects
elderly patients, with only 5-15% of the patients above age 60 achieving a
durable remission. Promising treatments are steadily released, with yet
unknown resistance mechanisms. Hence, within this project, you will conduct
integrative analyses using various types of single-cell molecular data
sources to identify mechanisms driving clonal evolution and therapy
resistance. Within the newly established Leiden Center for Computational
Oncology, acute myeloid leukemia was chosen as one of the projects to
spearhead the development of novel computational tools that provide more
insight into tumor heterogeneity and tumor evolution under therapeutic
pressure. The activities of the PhD candidate are purely computational and
will be embedded within the Leiden Computational Biology Center (prof. M.
Reinders), and the department of Hematology (prof. H. Veelken, MD).


WHAT WE ASK

You hold a MSc degree in Bioinformatics, Statistics, Life Sciences, or a
similar area. You possess a strong background in data analytics, have
hands-on experience with applying machine learning methods, and you are
familiar with scripting languages such as R or Python. Knowledge of genetic
analyzation and transcriptomic studies are favored but not required. You
enjoy the pursuit of knowledge across multiple field, and you have an
optimistic and kind nature.


INTERESTED?
Please send your CV and motivation letter (deadline November 15th) to:
https://lumc.recruitee.com/l/en/o/phd-candidate-tumor-heterogeneity-in-acute-myeloid-leukemia-d20bhmr02/c/new

Kind regards,

Erik van den Akker

Leiden University Medical Centre

Molecular Epidemiology
<http://www.molepi.nl/en/people/people_item/t/erik_van_den_akker>

Einthovenweg 20, 2333 ZC, Leiden, The Netherlands

Building 2 [Research], Room S5-38

tel: +31 (0)71 526 85 57


Delft University of Technology

Delft Bioinformatics Lab
<https://www.tudelft.nl/ewi/over-de-faculteit/afdelingen/intelligent-systems/pattern-recognition-bioinformatics/the-delft-bioinformatics-lab/>

Van Mourik Broekmanweg 6, 2628 XE, Delft, The Netherlands

Building 28 [WI], Room W5.820

tel: +31 (0)15 278 55 17
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