Postdoc – Computational Cancer Epigenomics / Single-Cell Analysis / Machine Learning

St. Anna Children's Cancer Research Institute (CCRI)
Integrative Analysis of Pediatric Cancer
Austria Vienna
cancerbits.github.io

Description

We are looking for computational biologists at post-doctoral level who want to pursue ambitious research in cancer and developmental genomics.

Our group (science.ccri.at/research/research-areas/integrative-analysis) at St. Anna Children’s Cancer Research Institute (CCRI) strives to understand cellular development in cancer. Our projects center around two core themes:
* Integrative analysis of tumors / tumor models using multi-omics technologies (transcriptomics, epigenomics, proteomics). We extend our previous work on histiocytoses, and aim to dissect intra-tumor development in other solid tumors (neuroblastoma, sarcoma, lymphoma).
* Using computational modelling to connect complex biomolecular data to interpretable biological mechanisms. To this end, we apply machine learning to large data collections and we implement interfaces that ease access to these methods for experimental scientists.

Relevant publications: Halbritter et al. Cancer Discovery 2019; Mass, …, Halbritter, et al. Science 2016; Barakat, Halbritter, et al. Cell Stem Cell 2018, Farlik, Halbritter, et al. Cell Stem Cell 2016

As a postdoc, you will:
* Join a recently established, small, and highly cooperative team, dedicated to support your personal and professional development.
* Take charge of multiple projects within both themes described above. You bring in your own ideas and expertise to make the projects your own.
* Analyze multi-omics data, including single-cell RNA-seq and ATAC-seq, ChIP-seq, RRBS/WGBS, and quantitative proteomics from pediatric solid tumors.
* Write code to scrape public data (GEO, TCGA, GTEx, etc.), train conventional or deep machine learning models, and apply them to your single-cell data.
* Interpret, present, and discuss your results with biologists and clinical researchers locally and internationally.
* Independently monitor the literature and community resources to keep abreast latest developments and to identify information, data, and methods to integrate in your own work.
* Write papers, visit conferences, review papers, apply for fellowships, and contribute to grants.
* Contribute to the supervision of junior group members.


Qualifications

* PhD in a relevant subject (bioinformatics, genomics, molecular biology, cancer, etc.)
* Essential: At least one first-author publication in a reputable journal.
* Essential: Good programming skills (R or Python); good understanding of statistics. Desirable: Comfortable working in a remote Unix computing environment.
* Essential: Extensive experience with multi-omics data analysis (e.g., RNA-seq, ATAC-seq). Desirable: Experience with single-cell technologies.
* Essential: Experience with commonly used machine learning frameworks. Desirable: Proficiency with deep learning methods.
* Good knowledge of molecular biology and interest in cancer. Excellent verbal and written communication skills in English (German not required).
* An exceptional level of enthusiasm, determination, and creativity.
* Independence, critical thinking, and ideas.


Start date

As soon as possible

How to Apply

Applications must include a motivation letter, curriculum vitae, list of publications (please mark/explain your three top contributions), and contact details of three references. Please send your application or inquiries only by e-mail to Dr. Florian Halbritter, hr@ccri.at. All applications received before October 30th, 2019, will be considered. The position shall remain open until a suitable candidate is found. Start date is flexible.


Contact

hr@ccri.at