Senior Bio Machine Learning Scientist - 136085

Overview

The Ideker Laboratory is in the Division of Human Genetics and Precision Medicine at UC San Diego School of Medicine. We are a vibrant research team of 30-40 staff, postdocs, graduate students, and undergraduate students known for its dynamic and collaborative environment. We perform bioinformatics research coupled with wet-lab investigations, working in the areas of network biology, data-driven hierarchical modeling, and machine learning applied to biomedicine. We also support multiple open-source software projects, some with 100K+ users. One of the main research goals of the Ideker Lab is to create artificially intelligent, mechanistic models of cancer for translation of patient data to precision diagnosis and treatment. We are advancing this goal by developing "visible" predictive machine learning approaches to model the flow of genetic information to translate genotype to phenotype and, importantly, to identify the molecular functions and mechanisms by which these predictions are made.

The Ideker Laboratory is recruiting a Senior BioMachine Learning Scientist to lead machine learning R&D for the ADAPT project, a new precision cancer therapy initiative funded by ARPA-H. The overall goal of the ADAPT project is to use advanced AI/ML technologies to deliver the right therapy to the right patients at the right time. ADAPT will revolutionize cancer treatment by using predictive biomarkers and interpretable AI/ML to create dynamical cancer treatment strategies and personalized therapies for patients with metastatic cancers.

Responsibilities

• Lead the design and implementation of deep learning approaches for drug recommendation in cancer.
• Serve as a computational lead in interdisciplinary teams, collaborating with biologists, oncologists, statisticians, and other computational/ML scientists to translate computational findings into therapeutic strategies.
• Design, debug, and optimize algorithms and computational techniques to analyze complex, multimodal datasets, including genomic, proteomic, and transcriptomic, and clinical data.
• Develop multi-modal data fusion pipelines for biomarker discovery and therapy recommendation.
• Create and validate computational tools to track tumor changes and adapt therapy plans in real-time using insights from biomarker data.
• Create and oversee a central benchmarking platform for standardizing AI/ML models.
• Contribute to the creation and maintenance of a central cancer treatment and analysis platform, ensuring accurate and timely data availability for clinicians and researchers.
• Provide guidance to junior researchers, including PhD students and postdocs, fostering expertise in bioML and its applications in oncology.
• Lead the development and dissemination of robust, scalable bioinformatics software, ensuring alignment with FAIR data principles and accessibility to the broader research community.
• Prepare detailed reports, publications, and presentations showcasing progress on ADAPT program goals, and represent the lab at national and international conferences.
• Collaborate closely with the Ideker Lab's Program Manager to identify and pursue new funding opportunities, align lab objectives with emerging trends in precision medicine, and contribute to grant proposals to support long-term research initiatives.
• In addition to the main ADAPT initiative, we expect that this position will work on and potentially lead other projects within the Ideker Lab research portfolio as needed.

Minimum Qualifications

• Nine years of related experience, education/training, OR a Bachelor's degree in related area plus five years of related experience/training.
• Advanced knowledge of HPC / data science / CI.
• Highly advanced skills, and demonstrated experience associated with one or more of the following: HPC hardware and software power and performance analysis and research, design, modification, implementation and deployment of HPC or data science or CI applications and tools of large-scale scope.
• Demonstrated ability to regularly, effectively communicate with unit-level management.
• Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences.
• In depth skills and experience in independently resolving complex computing / data / CI problems using introductory and / or intermediate principles.
• Self-motivated and works independently and as part of a team.
• Advanced experience working in a complex computing / data / CI environment encompassing all or some of the following: HPC, data science infrastructure and tools / software, and diverse domain science application base.
• In depth ability to successfully work and / or lead multiple concurrent projects. Demonstrated research and technology project leadership and management skills.
• In depth experience assessing a broad spectrum of technical and research needs and demands and establish priorities, delegate and / or lead development of solutions to meet such needs.
• Demonstrated advanced experience in one or more of the following: optimizing, benchmarking, HPC performance and power modeling, analyzing hardware, software, and applications for HPC / data / CI.
• Advanced knowledge of deep learning model architectures and modern AI/ML technologies.

Preferred Qualifications

• Knowledge of modern cancer biology, omics, and systems biology.
• Demonstrated ability to initiate research proposals and acquire funding.

Special Conditions

• Employment is subject to a criminal background check.

Pay Transparency Act

Annual Full Pay Range: $119,400 - $230,800 (will be prorated if the appointment percentage is less than 100%)

Hourly Equivalent: $57.18 - $110.54

Factors in determining the appropriate compensation for a role include experience, skills, knowledge, abilities, education, licensure and certifications, and other business and organizational needs. The Hiring Pay Scale referenced in the job posting is the budgeted salary or hourly range that the University reasonably expects to pay for this position. The Annual Full Pay Range may be broader than what the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable).

Additional Information

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