Tweet
In cancer biology, we are witnessing an explosion in the number of techniques and datasets being produced to measure elements within cells at a genome-scale. These range from transcript expression, mutations, proteins, metabolites, and microRNAs, to name a few. Translating these datasets into biological hypothesis has become a challenge that requires both computational expertise in developing, applying, and troubleshooting software and also expertise in placing computational results into the context of the biology being studied. Accordingly, we are seeking a computational biologist/bioinformatician that is proficient with genomics data and is interested in working in a highly interactive interdisciplinary team in cancer biology.
There are many opportunities to develop research projects that coordinate with the strengths of the research group. From the computational side, these strengths include data integration, gene function prediction, network inference, and drug sensitivity modeling. From the cancer biology side, we have focused strengths in prostate and bladder cancers, from basic research in cell culture and mouse models to clinical treatment. The group has a strong translational focus with access to clinical samples and clinicians eager to integrate genomic medicine into their treatment strategies.
This position will be primarily under the supervision of Dr. James Costello, Assistant Professor in the Department of Pharmacology. Secondary supervision will be provided by Dr. Scott Cramer, Professor in the Department of Pharmacology, and Dr. Dan Theodorescu, Professor of Surgery and Pharmacology, and Director of the Cancer Center.
Minimum requirements are a PhD degree in Bioinformatics, Computer Science, Computational Biology or related science. A successful candidate will have research experience and demonstrated expertise in developing algorithms for computational biology applications and analysis of next gen sequencing data. A successful candidate must also have excellent communication skills in translating the results of computational analyses to wet lab scientists.
Ability to develop and implement algorithms in a programming language (e.g., C, Java) or scripting language (e.g., Perl, Python). Experience using standard bioinformatics tools and database development (e.g., MySql).
A successful candidate should have some exposure to wet lab science, preferably having performed their own experiments
Please apply through the following website:
There are many opportunities to develop research projects that coordinate with the strengths of the research group. From the computational side, these strengths include data integration, gene function prediction, network inference, and drug sensitivity modeling. From the cancer biology side, we have focused strengths in prostate and bladder cancers, from basic research in cell culture and mouse models to clinical treatment. The group has a strong translational focus with access to clinical samples and clinicians eager to integrate genomic medicine into their treatment strategies.
This position will be primarily under the supervision of Dr. James Costello, Assistant Professor in the Department of Pharmacology. Secondary supervision will be provided by Dr. Scott Cramer, Professor in the Department of Pharmacology, and Dr. Dan Theodorescu, Professor of Surgery and Pharmacology, and Director of the Cancer Center.
Minimum requirements are a PhD degree in Bioinformatics, Computer Science, Computational Biology or related science. A successful candidate will have research experience and demonstrated expertise in developing algorithms for computational biology applications and analysis of next gen sequencing data. A successful candidate must also have excellent communication skills in translating the results of computational analyses to wet lab scientists.
Ability to develop and implement algorithms in a programming language (e.g., C, Java) or scripting language (e.g., Perl, Python). Experience using standard bioinformatics tools and database development (e.g., MySql).
A successful candidate should have some exposure to wet lab science, preferably having performed their own experiments
Please apply through the following website:
