Mount Sinai School of Medicine
EMPLOYER: Genetics and Genomic Sciences, Mount Sinai School of Medicine
LOCATION: New York, United States
POSTED: Oct 07, 2012
EXPIRES: Jan 05, 2013
JOB TYPE: Postdoctoral researcher
SECTOR: Academia
HOURS: Full time
Description
Postdoc Positions
Two postdoc positions are currently available in Dr. Rui Chang’s lab:
General guideline
Prospective candidates should have a recent PhD degree in computer science, mathematics, bioinformatics/computational biology discipline and high motivation to pursue independent research in computational biology. Applicants are expected to have a solid background in programming and computational techniques, with a working knowledge of molecular biology and genetics being highly desirable.
Specific guideline
Position 1: Applicants who desired to focus on method developments and software development:
Prospective candidates should have a recent PhD degree in computer science specialized in machine learning, mathematics, statistics or physics. Strong working experiences in Bayesian networks and other graphical models is highly preferred. Candidate must have strong programming skills in C/C++/Java, Matlab and R. Programming skills in other language is a plus. Basic knowledge in biology and hands-on experience in computational biology is highly desired but not required. The candidate will be responsible for developing cutting-edge machine learning approaches based on graphical models and other mathematical models, and is expected to develop software platforms towards real-world human disease network modeling and drug target prediction by working closely with disease modeling team.
Position 2: Applicants who desired to focus on real-world disease modeling:
Prospective candidates should have a recent PhD degree in computer science, bioinformatics (computational biology) or biology science. Candidate must have strong knowledge in biology, genomics, and hands-on experience in computational biology projects involves analyzing and integrating omics data. Candidate should have a good programming skills in C/Java, Matlab or R. Programming skills in other language is a plus. Basic knowledge about graphical models, machine learning approaches is required. Strong understanding on Bayesian network is highly desired, but not required. The candidate will be responsible for integrating and analyzing multi-scale omics data and leverage cutting-edge method to reconstruct disease network and drug targets validation by working closely with method development team and laboratory collaborators.
Note:
Exceptional candidate have both strong machine learning background and biology knowledge can be considered to work cross projects and fields.
Dr. Rui Chang’s Lab
Computational Biology, Systems Biology, Network Biology, Gene Expression/Phenotype Prediction, Regulatory Network and Signaling Pathway Reconstruction, Bayesian Networks,
Research Interests
The researches in Dr. Chang’s lab broadly cover the topics within the field of Systems Biology. In particular, we are focused on dissecting the gene regulatory networks and signaling pathways in human diseases, such as cancer and human developments, such as human embryonic, adult stem cells, by developing and integrating cutting-edge reverse engineering approaches and statistical models. Secondly, we are interested in reconstructing genome-wide and context-specific predictive network models of human cells to interrogate impact of underpinning biological process to the development of both physiological and pathological phenotypes and generate in-silico hypothesis in combination with laboratory validations towards next generation genetic therapy.
To apply
Contact:
Please send CV and three reference letters to rui.r.chang@mssm.edu