The Luna lab is affiliated with the National Library of Medicine and National Cancer Institute. The lab’s dual ambitions are to make biomedical data and information accessible and advance cancer research to help people live longer, healthier lives. We seek highly motivated and skilled candidates to join our team with the goal of understanding how researchers interpret large data sets and enable them to explore and gain insight from data sets through interactive systems to advance healthcare.

QUALIFICATIONS

Essential:

• PhD in a relevant field, including: Statistics, Mathematics, Data Science, Computer Science/Engineering, Electrical Engineering, Medical Informatics, or a degree related to Biology with substantial experience in computational and statistical work. Individuals in the final stages of PhD submission will be considered as well as PhD graduates within 5 years of graduation.
• Excellent knowledge of theory and practice of LLM and foundation model, as well as deep learning neural networks
• Excellent coding skills in modeling and conversational interface design for real-time interaction (e.g., PyTorch/TensorFlow and Python proficiency)
• Rapid prototyping environment such as Python; C++ and parallel programming (e.g., CUDA)
• Experience multimodal generative language models, personalized LLM, and/or fine-tuning LLMs with/for reinforcement learning planning
• Technical expertise in machine learning and/or mathematical modeling
• An interest in applying computational methods to biological problems
• A demonstrated ability to generate and pursue independent research ideas
• Excellent communication skills, written and verbal as evidenced by publications, preprints, and/or conference presentations in conversational artificial intelligence venues (e.g., CoLing, EMNLP, ACL, NAACL, IJCAI, ICLR, NeurIPS, AAAI, CVPR, IEEE, JAMIA, etc)
• Dedication to reproducible research and open science

Preffered:

• Ph.D. thesis in neural conversational systems or closely related area
• Foundational knowledge in Bioinformatics, Systems Biology, and/or similar fields
• Foundational knowledge in Mathematics, Statistics, and/or Data Science
• Familiarity with software development practices and high-performance computing
• Experience with analysis using the R programming language (the lab has a significant, existing codebase in R)
• Experience with using network-based analyses (graph theory) and software/resources (graph and/or pathway databases) is highly desirable
• Experience with biomedical ontologies
• Development and execution of annotation tasks with teams of experts
• Experience working in collaborative interdisciplinary environments

Please refer the Job description for details