Summary

The Lester and Sue Smith Breast Center at Baylor College of Medicine is seeking a highly motivated and skilled research scientist to join our team, focusing on computational proteogenomics and its applications in cancer research. This non-tenure track assistant professor position is centered on advancing research in the dynamic and evolving field of computational cancer proteogenomics, with an emphasis on developing and using innovative computational methods to address critical cancer biology and clinical questions. The successful candidate will be instrumental in driving research projects, collaborating with interdisciplinary teams, and contributing to the development of innovative computational algorithms and tools.

Job Duties

Clearly describe the position so candidates have a clear understanding of the type of work they will be expected to perform and the environment in which they will work.

• Identify the setting in
• Lead and conduct innovative research in omics data analysis and integration, with a focus on cancer proteogenomics.
• Develop and apply computational tools and methods for the analysis of large-scale proteomics, genomics, and other omics datasets.
• Collaborate with interdisciplinary teams within the institution and with external partners to advance cancer research.
• Mentor junior researchers and students involved in cancer proteogenomics projects, fostering an environment of learning and professional growth.
• Contribute to grant writing and securing funding for research projects.
• Publish research findings in high-impact peer-reviewed journals and present at national and international conferences.
• Develops novel proteomics and proteogenomics data analysis methods and algorithms.
• Researches and evaluates newly published methods and algorithms for integrating into our existing proteogenomics data analysis tools.
• Applies established tools and methods to cancer proteomics, immunopeptidomics, and proteogenomics studies.
• Publishes methods, software, and application papers.
• Provides technical guidance, work direction and training to other lab members on areas of expertise.
• Performs other job-related duties as assigned.
• which the faculty member will work (e.g., hospitals, clinics, labs) and the individual(s) to whom he or she will report.
• Articulate clinical, research and/or teaching responsibilities of the position.
• Delineate supervisory responsibilities (if any) for staff, students, trainees and/or other faculty members.

Minimum Qualifications

• PhD in Bioinformatics, Computational Biology, Systems Biology, or a closely related field.
• Demonstrated experience in omics data analysis and integration, specifically in cancer proteogenomics.
• Strong publication record in relevant fields.
• Experience in proteomics and/or multi-omics data analysis as demonstrated by peer-reviewed publications and/or software packages.
• Knowledge about statistics and machine learning algorithms.
• Programming in UNIX/LINUX environment
• Strong presentation skills and written/verbal communication skills.
• Proficiency in programming languages such as R, Python, or similar.
• Experience with machine learning and statistical data analysis.
• Excellent communication and collaboration skills.
• Commitment to teaching, mentoring, and diversity in the scientific community.