Stanford Blood Center
Research Scientist - Interpretability (1 Year Fixed Term)
Stanford Blood Center, Stanford, California, United States, 94305
Overview
The Enigma Project is a research organization based in the Department of Ophthalmology at Stanford University School of Medicine dedicated to understanding the computational principles of natural intelligence using the tools of artificial intelligence. Leveraging advances in neurotechnology and machine learning, this project aims to create a foundation model of the brain, capturing the relationship between perception, cognition, behavior, and the activity dynamics of the brain. This initiative seeks to offer insights into the algorithms of the brain while serving as a resource for aligning artificial intelligence models with human-like neural representations. We seek talented individuals specializing in mechanistic interpretability to develop novel methods and scalable systems for analyzing and interpreting these models, helping us understand how the brain represents and processes information. The role combines rigorous engineering practices with cutting-edge research in model interpretability at the intersection of neuroscience and artificial intelligence. Role & Responsibilities
Lead research initiatives in the mechanistic interpretability of foundation models of the brain Develop novel theoretical frameworks and methods for understanding neural representations Design and guide interpretability studies that bridge artificial and biological neural networks Apply advanced techniques for circuit discovery, feature visualization, and geometric analysis of high-dimensional neural data Collaborate with neuroscientists to connect interpretability findings with biological principles Mentor junior researchers and engineers in interpretability methods Help shape the research agenda of the interpretability team Other duties may also be assigned What we offer
An environment to pursue fundamental research questions in AI and neuroscience interpretability Access to unique datasets spanning artificial and biological neural networks State-of-the-art computing infrastructure Competitive salary and benefits package Collaborative environment at the intersection of multiple disciplines Location at Stanford University with access to its world-class research community Application: In addition to applying to the position, please send your CV and one-page interest statement to recruiting@enigmaproject.ai Application
Notes:
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory for all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. Desired Qualifications
Ph.D. in Computer Science, Machine Learning, Computational Neuroscience, or related field plus 2+ years post-Ph.D. research experience At least 2+ years of practical experience in training, fine-tuning, and using multi-modal deep learning models Strong publication record in top-tier machine learning conferences and journals, particularly in multi-modal modeling Strong programming skills in Python and deep learning frameworks Demonstrated ability to lead research projects and mentor others Ability to work effectively in a collaborative, multidisciplinary environment Preferred Qualifications
Background in theoretical neuroscience or computational neuroscience Experience with processing and analyzing large-scale, high-dimensional data from different sources Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and their ML services Familiarity with big data and MLOps platforms (e.g., MLflow, Weights & Biases) Familiarity with training, fine-tuning, and quantization of LLMs or multimodal models using common techniques and frameworks (LoRA, PEFT, AWQ, GPTQ, or similar) Experience with large-scale distributed model training frameworks (e.g., Ray, DeepSpeed, HF Accelerate, FSDP) Education & Experience (REQUIRED):
Bachelor\'s degree and five years of relevant experience, or combination of education and relevant experience. Knowledge, Skills and Abilities (REQUIRED): Expert knowledge of the principles of engineering and related natural sciences Demonstrated project leadership experience Demonstrated experience leading and/or managing technical professionals Certifications & Licenses:
None Physical Requirements
Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects up to 10 pounds; occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully Rarely kneel/crawl, climb ladders/scaffolds, reach/work above shoulders, use a telephone, write by hand, sort/file paperwork or parts, operate controls, lift/carry/push/pull objects up to 40 pounds Consistent with its obligations under the law, reasonable accommodations are available for employees with a disability Working Conditions
May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, allergens/biohazards/chemicals/asbestos, confined spaces, working at heights, temperature extremes, heavy metals, unusual work hours or overtime, and inclement weather May require travel The expected pay range for this position is $156,560 to $180,039 annually. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as scope and responsibilities, qualifications, departmental budget, internal equity, location, and market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the rewards package. The Cardinal at Work website provides detailed information on Stanford’s benefits. Specifics about the rewards package may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring accommodations for any part of the application or hiring process should contact Stanford University Human Resources via the provided contact form. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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The Enigma Project is a research organization based in the Department of Ophthalmology at Stanford University School of Medicine dedicated to understanding the computational principles of natural intelligence using the tools of artificial intelligence. Leveraging advances in neurotechnology and machine learning, this project aims to create a foundation model of the brain, capturing the relationship between perception, cognition, behavior, and the activity dynamics of the brain. This initiative seeks to offer insights into the algorithms of the brain while serving as a resource for aligning artificial intelligence models with human-like neural representations. We seek talented individuals specializing in mechanistic interpretability to develop novel methods and scalable systems for analyzing and interpreting these models, helping us understand how the brain represents and processes information. The role combines rigorous engineering practices with cutting-edge research in model interpretability at the intersection of neuroscience and artificial intelligence. Role & Responsibilities
Lead research initiatives in the mechanistic interpretability of foundation models of the brain Develop novel theoretical frameworks and methods for understanding neural representations Design and guide interpretability studies that bridge artificial and biological neural networks Apply advanced techniques for circuit discovery, feature visualization, and geometric analysis of high-dimensional neural data Collaborate with neuroscientists to connect interpretability findings with biological principles Mentor junior researchers and engineers in interpretability methods Help shape the research agenda of the interpretability team Other duties may also be assigned What we offer
An environment to pursue fundamental research questions in AI and neuroscience interpretability Access to unique datasets spanning artificial and biological neural networks State-of-the-art computing infrastructure Competitive salary and benefits package Collaborative environment at the intersection of multiple disciplines Location at Stanford University with access to its world-class research community Application: In addition to applying to the position, please send your CV and one-page interest statement to recruiting@enigmaproject.ai Application
Notes:
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory for all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. Desired Qualifications
Ph.D. in Computer Science, Machine Learning, Computational Neuroscience, or related field plus 2+ years post-Ph.D. research experience At least 2+ years of practical experience in training, fine-tuning, and using multi-modal deep learning models Strong publication record in top-tier machine learning conferences and journals, particularly in multi-modal modeling Strong programming skills in Python and deep learning frameworks Demonstrated ability to lead research projects and mentor others Ability to work effectively in a collaborative, multidisciplinary environment Preferred Qualifications
Background in theoretical neuroscience or computational neuroscience Experience with processing and analyzing large-scale, high-dimensional data from different sources Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and their ML services Familiarity with big data and MLOps platforms (e.g., MLflow, Weights & Biases) Familiarity with training, fine-tuning, and quantization of LLMs or multimodal models using common techniques and frameworks (LoRA, PEFT, AWQ, GPTQ, or similar) Experience with large-scale distributed model training frameworks (e.g., Ray, DeepSpeed, HF Accelerate, FSDP) Education & Experience (REQUIRED):
Bachelor\'s degree and five years of relevant experience, or combination of education and relevant experience. Knowledge, Skills and Abilities (REQUIRED): Expert knowledge of the principles of engineering and related natural sciences Demonstrated project leadership experience Demonstrated experience leading and/or managing technical professionals Certifications & Licenses:
None Physical Requirements
Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects up to 10 pounds; occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully Rarely kneel/crawl, climb ladders/scaffolds, reach/work above shoulders, use a telephone, write by hand, sort/file paperwork or parts, operate controls, lift/carry/push/pull objects up to 40 pounds Consistent with its obligations under the law, reasonable accommodations are available for employees with a disability Working Conditions
May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, allergens/biohazards/chemicals/asbestos, confined spaces, working at heights, temperature extremes, heavy metals, unusual work hours or overtime, and inclement weather May require travel The expected pay range for this position is $156,560 to $180,039 annually. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as scope and responsibilities, qualifications, departmental budget, internal equity, location, and market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the rewards package. The Cardinal at Work website provides detailed information on Stanford’s benefits. Specifics about the rewards package may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring accommodations for any part of the application or hiring process should contact Stanford University Human Resources via the provided contact form. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
#J-18808-Ljbffr