Job description

Working at Yale means contributing to a better tomorrow. Whether you are a current resident of our New Haven-based community, eligible for opportunities through the New Haven Hiring Initiative, or a newcomer, interested in exploring all that Yale has to offer, your talents and contributions are welcome. Discover your opportunities at Yale! Overview The Department of Neurosurgery is seeking an experienced AI/ML professional and a knowledgeable AI enthusiast to help the ARIA team develop, use, and evaluate AI and apply it to deliver breakthrough research and applications at an unprecedented speed and scale. Guides projects within the research core, supporting core technologies, managing experimental design and data analysis. The Yale School of Medicine Department of Neurosurgery is seeking an AI researcher to develop machine-learning methods for large-scale human brain data within the Aligning Research to Impact Autism (ARIA) program. The work will focus on neural decoding, forecasting, representation learning, and multimodal modeling using intracranial EEG (iEEG/ECoG), scalp EEG, fNIRS, fMRI, and related data. The successful candidate will be an individual who enjoys working both independently and cooperatively with others, from a broad set of disciplinary backgrounds, on multiple projects involving a wide variety of topics and analytical tools. Job Duties: Develop, train, and evaluate machine-learning models for multimodal human brain data. Build models for neural representation learning, forecasting, decoding, and cross-modal analysis. Contribute to the development of scalable brain foundation models across subjects, recording modalities, and tasks. Work with large datasets and optimize training pipelines for GPU and HPC environments. Collaborate with clinicians, neuroscientists, engineers, and other researchers on study design and analysis. Maintain clear, reproducible code and documentation for model development and evaluation. Contribute to manuscripts, conference presentations, and grant-related research activities. Provide technical guidance to students and research staff when appropriate. Required Skills and Abilities 1. Proven experience developing machine-learning or deep-learning models. Proven experience with distributed or multi-GPU training and memory-efficient model training. 2. Familiarity with tools such as Slurm, CUDA, Docker or Apptainer, Conda, and scientific computing clusters. 3. Strong Python programming skills and practical experience with PyTorch or a comparable deep-learning framework. 4. Proven experience with modern neural-network architectures such as Transformers, self-supervised learning, representation learning, generative models, or foundation models. 5. Proven experience training models on GPUs and working in Linux and high-performance computing environments. Preferred Skills and Abilities 1. Proven experience with neural or physiological data, including iEEG/ECoG, EEG, fNIRS, fMRI, MEG, or related biosignals. 2. Proven experience with time-series modeling, neural forecasting, multimodal learning, or brain-computer interface research. 3. Proven experience with efficient attention or large-model training methods, including scaled-dot-product attention, FlashAttention, mixed precision, or activation checkpointing. 4. A research record in machine learning, computer vision, natural language processing, computational neuroscience, biomedical AI, or a related area. 5. Proven experience developing machine-learning or deep-learning models for research applications. Principal Responsibilities 1. User Training: Provide advanced training and guidance to users of the research core. 2. Experiment Support: Collaborate with researchers on experimental design, execution, data analysis, and troubleshooting within the research core. 3. Facility/Instrument Support: Manage and oversee research projects within the research core. 4. Technique Development: Lead the implementation and optimization of advanced techniques and methodologies and develop standard operating procedures for research core services. 5. Data Analysis/Interpretation: Analyze and interpret complex scientific data, generating meaningful insights and recommendations. 6. Equipment Procurement: Assist in the selection, acquisition, and maintenance of research core equipment. 7. Professional Development: Stay updated with emerging research trends and technologies. Participate in professional development activities and scientific conferences. 8. Scientific Participation: Contribute scientific data for manuscript preparation and grant proposals 9. Staff Training and Mentoring: Contribute to the training and mentoring of junior staff members. 10. Vendor Relations: Manage vendor relationships, negotiates contracts, and evaluates new technologies for optimal procurement processes. 11. Education and Outreach: Contribute to education and outreach activities within the core, including tours, events, etc. Required Education and Experience Bachelor’s degree in a related discipline and four years of related experience or an equivalent combination of skills, education, and experience. Job Posting Date 10/14/2026 Job Category Professional Bargaining Unit NON Compensation Grade Administration & Operations Compensation Grade Profile Supervisor; Senior Associate (24) Salary Range $68,000.00 - $120,500.00 Benefits A general description of the benefits to be offered with this Managerial & Professional position is available at: Yale Benefits Time Type Full time Duration Type Staff Fixed Duration (Fixed Term) Work Model Hybrid Background Check Requirements All candidates for employment will be subject to pre-employment background screening for this position, which may include motor vehicle, DOT certification, drug testing and credit checks based on the position description and job requirements. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process visit "Learn about background checks" under the Applicant Support Resources section of Careers on the It's Your Yale website. Health Requirements Certain positions have associated health requirements based on specific job responsibilities. These may include vaccinations, tests, or examinations, as required by law, regulation, or university policy. Posting Disclaimer Salary offers are determined by a candidate’s qualifications, experience, skills, and education in relation to the position requirements, along with the role’s grade profile and current internal and external market conditions. The intent of this job description is to provide a representative summary of the essential functions that will be required of the position and should not be construed as a declaration of specific duties and responsibilities of the position. Employees will be assigned specific job-related duties through their hiring department. The University is committed to basing judgments concerning the admission, education, and employment of individuals upon their qualifications and abilities and seeks to attract to its faculty, staff, and student body qualified persons from a broad range of backgrounds and perspectives. In accordance with this policy and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against any individual on account of that individual’s sex, sexual orientation, gender identity or expression, race, color, national or ethnic origin, religion, age, disability, status as a special disabled veteran, veteran of the Vietnam era or other covered veteran. Inquiries concerning Yale's Policy Against Discrimination and Harassment may be referred to the Office of Institutional Equity and Accessibility (OIEA). Note Yale University is a tobacco-free campus.

Requirements

Must-haves

Develop, train, and evaluate machine-learning models for multimodal human brain data.
Build models for neural representation learning, forecasting, decoding, and cross-modal analysis.
Contribute to the development of scalable brain foundation models across subjects, recording modalities, and tasks.
Work with large datasets and optimize training pipelines for GPU and HPC environments.
Collaborate with clinicians, neuroscientists, engineers, and other researchers on study design and analysis.
Maintain clear, reproducible code and documentation for model development and evaluation.
Contribute to manuscripts, conference presentations, and grant-related research activities.
Provide technical guidance to students and research staff when appropriate.
Required Skills and Abilities
Proven experience developing machine-learning or deep-learning models. Proven experience with distributed or multi-GPU training and memory-efficient model training.
Familiarity with tools such as Slurm, CUDA, Docker or Apptainer, Conda, and scientific computing clusters.
Strong Python programming skills and practical experience with PyTorch or a comparable deep-learning framework.
Proven experience with modern neural-network architectures such as Transformers, self-supervised learning, representation learning, generative models, or foundation models.
Proven experience training models on GPUs and working in Linux and high-performance computing environments.
Proven experience with neural or physiological data, including iEEG/ECoG, EEG, fNIRS, fMRI, MEG, or related biosignals.
Proven experience with time-series modeling, neural forecasting, multimodal learning, or brain-computer interface research.
Proven experience with efficient attention or large-model training methods, including scaled-dot-product attention, FlashAttention, mixed precision, or activation checkpointing.
A research record in machine learning, computer vision, natural language processing, computational neuroscience, biomedical AI, or a related area.
Proven experience developing machine-learning or deep-learning models for research applications.
Principal Responsibilities
User Training: Provide advanced training and guidance to users of the research core.
Experiment Support: Collaborate with researchers on experimental design, execution, data analysis, and troubleshooting within the research core.
Facility/Instrument Support: Manage and oversee research projects within the research core.

Nice-to-haves

Preferred Skills and Abilities

Application prep

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Keywords to mirror

aimldockerpythonmachine learningaccessibility

Platform: phenom
Effort: medium

Benefits

Benefits detected in the listing.

Vision

Professional Development