"Interested in Postdoc Opportunities with our Lab?"

Refer to the document below for more information on our opportunities for Postdoc in Computational Biology for Ovarian Cancer Research.

Required Qualifications:

• A PhD in computational biology, bioinformatics, or an equivalent field with strong computational training.

• Proven experience in genomic data analysis (WES, RNA-seq, single-cell) and familiarity with public cancer databases.

• Proven experience in R and Python

To express your interest, please email your CV, two reference letters, and a one-page document outlining your research interests and how they align with this position to Dr. Avi Sahu at asahu@salud.unm.edu.

All UNM Students Interested in Postdoc, PhD, MD, and Undergraduate Research Experience at UNM TumorAI Lab, Reach Out to Avi Sahu at asahu@salud.unm.edu

Postdoc in Computational Biology for Ovarian Cancer Research 

Join a multidisciplinary team to pioneer computational methods for ovarian cancer prevention and treatment. This is a unique opportunity for a computational biologist to lead high-impact genomics projects and, if desired, be trained in cutting-edge AI/ML by world-class experts.

TumorAI lab (TumorAI.org) develops and applies novel AI and statistical methodologies to create new diagnostics and therapeutics for cancer.

The Opportunity & Your Role

You will help solve one of the most pressing challenges in gynecologic oncology: the "diagnostic limbo" caused by Variants of Uncertain Significance (VUS).

You will lead high-impact computational projects to refine and validate our lab's foundation models, Mutation2Text (a generative AI for variant interpretation) and SoMatt (a model for tumor genome interpretation).

Your primary goal will be to adapt these models for the precise prediction of ovarian cancer risk, therapy sensitivity, and patient survival. Your work will directly bridge computational predictions with clinical reality. You will collaborate closely with our team's gynecologic oncologists, genetic counselors, and wet-lab biologists to validate your predictions in vivo and organoid models.

Why Join

Unparalleled Mentorship This position is co-advised by Dr. Avi Sahu (AI and statistical methods), Dr. Christopher Amos (genetic susceptibility and statistical genetics), Dr. Sarah Adams (gynecologic oncology and clinical research). Research team includes : Dr. Mara Steinkamp (Organoids and mouse models), and Dr. Jun S Liu (Statistical methods, Harvard).

Career Development Our lab has a proven track record of launching independent careers. Members have secured prestigious Young Investigator and career development awards (K99, AAI Intersect Award, K12, etc.), and transitioned to faculty position. We provide dedicated mentorship and expect postdocs to learn to apply for competitive NIH, NSF, or foundation grants to build their own research trajectories.

Compensation : A competitive starting salary $70,000. Low cost of living (Albuquerque).

AI/ML upskilling track. Hands-on training in modern interpretable ML for genomics

Who We Are Looking For: We are seeking a candidate with a strong background in computational biology, bioinformatics, or a related field.

Required Qualifications:

• A PhD in computational biology, bioinformatics, or an equivalent field with strong computational training.
• Proven experience in genomic data analysis (WES, RNA-seq, single-cell) and familiarity with public cancer databases.
• Proven experience in R and Python

How to Apply: To express your interest, please email your CV, two reference letters, and a one-page document outlining your research interests and how they align with this position to Dr. Avi Sahu at asahu@salud.unm.edu. Visit TumorAI.org for additional career opportunities.