Computational Scientist

Translational Genomics Research Institute (TGen) is a Phoenix, Arizona-based non-profit organization which established itself as a leader in translational research and precision medicine. TGen’s mission is leveraging genomics and proteomics expertise and capabilities to deploy “multi-omic” solutions to accelerate the development of new medical diagnostics and innovative therapies for the prevention and treatment of human disease including cancer and neurological disorders. TGen is a part of City of Hope which is an NCI-designated Comprehensive Cancer Center. Through collaborations with COH clinicians and researchers we are eager to accelerate the speed with which research discoveries are utilized in a clinical setting.

The GarMiglio Lab ( led by Dr. Luciano Garofano (Assistant Professor) and Dr. Simona Migliozzi (Assistant Professor) at The Translational Genomics Research Institute ( located in Phoenix) is an interdisciplinary research group aimed at understanding the molecular mechanisms of cancer progression, metastasis, and resistance to therapy in solid tumors with particular focus on adult and pediatric brain tumors, lung, breast, melanoma and brain metastasis. Our groups combine patient biospecimens, computational approaches and experimental models to dissect cancer heterogeneity, identify functional and clinically relevant tumor subtypes in order to extract targetable molecular nodes with the final aim of developing more effective therapies that improve the survival outcome of cancer patients. Ongoing projects include: i) dissecting glioma ecosystem during evolution, ii) role of neurons-cancer crosstalk in non-CNS tumor progression, iii) reconstructing the spatiotemporal proteomic mosaicism in pediatric brain tumors.

We are looking for talented researchers to develop computational pipelines and implement data analytical models to integrate multi-omics data (spatial single cell transcriptomics, single cell and bulk genomics, epigenetics and proteomics). Candidates with expertise in machine learning approaches and reconstruction of gene/protein regulatory networks with knowledge or strong interest in cancer biology are encouraged to apply.

The successful candidate will take a leadership role in ongoing projects as well as develop new research ideas. Specific duties will include, data analysis, interpretation of results, presentation of findings and preparation of peer reviewed manuscripts and grant proposals.

Required Qualifications:

• Master’s or PhD (optional) in Engineering, Computational Biology, Bioinformatics, Computer Science, Mathematics, Statistics, or related field.
• Deep proficiency or strong interest in molecular cancer biology.
• Knowledge of, or experience with, basic techniques and methods required by the position.
• Excellent communication and organizational skills.
• Ability to manage time and multitask effectively.

Preferred Qualifications:

• At least 1 year of research experience.
• Experience coding in bash, Python and/or R environments.
• Experience with Bioconductor packages.
• Confident operating high-performance cluster systems via schedulers such as SLURM or Torque/PBS

Please apply by emailing a cover letter (Statement of Research, optional), your CV and contact information for two references to [email protected] and [email protected]

Translational Genomics Research Institute (TGen) is a Phoenix, Arizona-based non-profit organization which established itself as a leader in translational research and precision medicine. TGen’s mission is leveraging genomics and proteomics expertise and capabilities to deploy “multi-omic” solutions to accelerate the development of new medical diagnostics and innovative therapies for the prevention and treatment of human disease including cancer and neurological disorders. TGen is a part of City of Hope which is an NCI-designated Comprehensive Cancer Center. Through collaborations with COH clinicians and researchers we are eager to accelerate the speed with which research discoveries are utilized in a clinical setting.

The GarMiglio Lab ( led by Dr. Luciano Garofano (Assistant Professor) and Dr. Simona Migliozzi (Assistant Professor) at The Translational Genomics Research Institute ( , located in Phoenix) is an interdisciplinary research group aimed at understanding the molecular mechanisms of cancer progression, metastasis, and resistance to therapy in solid tumors with particular focus on adult and pediatric brain tumors, lung, breast, melanoma and brain metastasis. Our groups combine patient biospecimens, computational approaches and experimental models to dissect cancer heterogeneity, identify functional and clinically relevant tumor subtypes in order to extract targetable molecular nodes with the final aim of developing more effective therapies that improve the survival outcome of cancer patients. Ongoing projects include: i) dissecting glioma ecosystem during evolution, ii) role of neurons-cancer crosstalk in non-CNS tumor progression, iii) reconstructing the spatiotemporal proteomic mosaicism in pediatric brain tumors.

We are looking for talented researchers to develop computational pipelines and implement data analytical models to integrate multi-omics data (spatial single cell transcriptomics, single cell and bulk genomics, epigenetics and proteomics). Candidates with expertise in machine learning approaches and reconstruction of gene/protein regulatory networks with knowledge or strong interest in cancer biology are encouraged to apply.

The successful candidate will take a leadership role in ongoing projects as well as develop new research ideas. Specific duties will include, data analysis, interpretation of results, presentation of findings and preparation of peer reviewed manuscripts and grant proposals.

Required Qualifications:

• Master’s or PhD (optional) in Engineering, Computational Biology, Bioinformatics, Computer Science, Mathematics, Statistics, or related field. Deep proficiency or strong interest in molecular cancer biology. Knowledge of, or experience with, basic techniques and methods required by the position. Excellent communication and organizational skills. Ability to manage time and multitask effectively.

Preferred Qualifications:

• At least 1 year of research experience. Experience coding in bash, Python and/or R environments. Experience with Bioconductor packages. Confident operating high-performance cluster systems via schedulers such as SLURM or Torque/PBS

Please apply by emailing a cover letter (Statement of Research, optional), your CV and contact information for two references to [email protected] and [email protected]