Job Description:
We are seeking an independent scientist to integrate large-scale patient-derived molecular profiling datasets with clinical and biological data, to identify sub-types in key cancer indications and assess the association of new therapies with those sub-types. Research will center on compound positioning via the integration of extensive publicly-available cancer profiling datasets and biological information (including pathways and PPI networks) with internally-generated pre-clinical and clinical profiling data. This position is intended to allow an experienced computational researcher the freedom to integrate public resources with the pre-clinical and translational inside-knowledge (including compound MOAs and synergies), and an opportunity to leverage the mentorship and expertise of a well-resourced research environment while exploring industry as a potential career prospect. The individual selected will benefit from regular interactions with cancer biology and computational biology research teams, including a strong group of machine learning, patient stratification and pre-clinical studies experts. Publications are highly encouraged. Mentorship and experimental (lab) support will be readily available through various Celgene functions/teams. The possibility exists for the position to be located either in Summit NJ (USA) or Seville (Spain). Prerequisites: PhD in computer science, physics, math, statistics or engineering
Additional Info:
[Click Here to Access the Original Job Post]
We are seeking an independent scientist to integrate large-scale patient-derived molecular profiling datasets with clinical and biological data, to identify sub-types in key cancer indications and assess the association of new therapies with those sub-types. Research will center on compound positioning via the integration of extensive publicly-available cancer profiling datasets and biological information (including pathways and PPI networks) with internally-generated pre-clinical and clinical profiling data. This position is intended to allow an experienced computational researcher the freedom to integrate public resources with the pre-clinical and translational inside-knowledge (including compound MOAs and synergies), and an opportunity to leverage the mentorship and expertise of a well-resourced research environment while exploring industry as a potential career prospect. The individual selected will benefit from regular interactions with cancer biology and computational biology research teams, including a strong group of machine learning, patient stratification and pre-clinical studies experts. Publications are highly encouraged. Mentorship and experimental (lab) support will be readily available through various Celgene functions/teams. The possibility exists for the position to be located either in Summit NJ (USA) or Seville (Spain). Prerequisites: PhD in computer science, physics, math, statistics or engineering
Requirements
Skills/Knowledge Required:- Demonstrated experience in patient stratification and machine learning is required.
- Demonstrated experience in data integration is required (continuous, categorical and relational)
- Competent programmer fluent in Unix/Linux, Perl or Python, and R or Matlab or equivalent is required
- Working knowledge and understanding of molecular and cell biology preferred
- Deep understanding of molecular profiling and associated platforms preferred
- Strong interpersonal, oral, and written communication skills in the English language
- Previous experience in cancer biology is a plus
Requeriments :
Skills :
- Cancer biology
- Cell Biology
- Lunix/Unix
- Machine Learning
- molecular biology
- Programing in Python
- Programming in Matlab
- Programming in PERL
- Programming in R
Areas :
Additional Info:
[Click Here to Access the Original Job Post]