Tumor-Microenvironment & AI (TumorAI) lab (AviSahuAI.com) at UNM Comprehensive Cancer Center seeks two postdoctoral researchers in AI and computational biology to join our interdisciplinary team. The lab focuses on improving cancer treatments by developing novel diagnostic methods and utilizing AI and statistical approaches. Our team is dedicated to developing computational approaches for drugs and gene targets by interfacing immuno-oncology with AI/statistical approaches.
Compensation: We offer a minimum starting salary of $70,000+, commensurate with computation skillset and experience. Albuquerque’s cost of living is low (e.g. 45% lower than NYC).
Our lab is against “cheap labor” and unjustified low salaries for postdocs. We believe in postdocs for their talent, professional, and technical skills (ref go.nature.com/3YS5P52).
Postdoctoral researchers will develop independent research projects aligning with our mission and contribute to ongoing projects in developing computational approaches for: 1) personalized approaches for targeting tumor heterogeneity, 2) new immunotherapeutic targets and agents by targeting tumor immune microenvironment, and 3) statistical analysis of single cell data. We offer interdisciplinary mentorship in oncology and immunology from Cancer Center researchers, and in AI and statistic from leaders from Harvard. Our lab has extensive expertise in obtaining Young investigator grants from NIH, Foundations, and Pharma and Tech companies, as well as UNMCCC is a leader in this part of the country with a track record junior researchers obtaining NCI grants. Postdoc researchers will be trained and encouraged to apply for grants and fellowships (e.g. Michelson Prize, NIH K, Burroughs Welcome Foundation ) to advancing their careers.
Learning and developing AI and statistical approaches for cancer research.
Analyzing clinical and genomic data.
Contributing to research publications and grants. Learn and apply for career development grants.
Attending relevant workshops to develop computational biology, bioinformatics, and computational immunology skills.
PhD in computer science, engineering, physics, data sciences, or a related field OR PhD life sciences, biology, immunology, or a related field with computational training.
Applicants are required to have prior computational training and experience in R or Python.
Excellent verbal and written communication skills.
Ability to work independently and as part of a team.
The Avi Sahu Lab at the UNM Cancer Center is seeking a driven and enthusiastic Data Analyst Technician to join our cutting-edge team. As a member of our interdisciplinary group, you will have the chance to work on developing innovative diagnostic methods and utilizing artificial intelligence to improve cancer treatments.
This is an excellent opportunity for students, who are looking to expand their knowledge and skills in AI/statistical approaches and contribute to the development of new cancer therapies. With the possibility of working with renowned researchers, Drs. Jun Liu and Keith Flaherty at Harvard, you will have the chance to grow and learn from the best in the field.
Collaborating with team members to understand clinical and genomic data produced
Applying existing and novel algorithms to data
Participating in scientific writing and data figure creation for research publications
Attending training and workshops to further develop your skills in computational biology, bioinformatics, and computational immunology.
Bachelor’s or Master’s degree in computer science, engineering, physics, data sciences, or life sciences (biology, immunology, etc.)
Basics experience in computational data analysis (e.g. R, Python).
Verbal and written communication skills.
Ability to work independently and as part of a team.
Join our team at the Avi Sahu Lab at UNM Cancer Center as an Undergraduate Technician and contribute to our goal of improving the understanding and treatment of cancer through computer intelligence. Work alongside our statistical and oncology experts from UNM and Harvard to develop cutting-edge AI and statistical approaches. This is an excellent opportunity for students looking to expand their knowledge and skills in computational research.
Pursuing a degree in computer science, engineering, biochemistry, chemistry, or math major
Knowledge of R or Python for computational data analysis
Minimum cumulative GPA of 3.0/4.0
Able to work a minimum of 10 hours per week
Collaborate with team members to analyze clinical and genomic data
Learn single cell data analysis
Learn and develop AI and statistical approaches