Scientist I - ML/AI algorithms for Multimodal Foundational Models for Gene Regulation

Scientist I – ML/AI algorithms for Multimodal Foundational Models for Gene Regulation
The mission of the Allen Institute is to understand the principles that govern life, and to advance health. Our creative and multi-dimensional teams focus on answering some of the biggest questions in bioscience. We accelerate foundational research, catalyze bold ideas, develop tools and models, and openly share our science to make a broad, transformational impact on the world. The mission of the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. Using a big science approach, we generate useful public resources, drive technological and analytical advances, and discover fundamental brain properties through the integration of experiments, modeling, and theory.
The Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) consortium strives to achieve a deep molecular and cellular understanding of the early pathogenesis of Alzheimer’s disease (AD). Leveraging advances in quantitative neuropathology and next-generation single cell molecular profiling technologies we are generating large-scale data sets from well-characterized donors that span the spectrum of AD pathology to comprehensively map human brain cell types across aging and disease. These data along with tools for their use are made freely and publicly available.
We seek to hire a Research Scientist to design modern machine learning methods to integrate multimodal data and describe disease trajectories and contribute to the mechanistic understanding of Alzheimer’s disease pathology. The successful candidate will have a strong background in computational biology, and experience developing deep generative models and Bayesian algorithms. In addition, the ideal candidate will either have experience in causal inference or gene regulatory network inference, or has worked on aspects of gene regulation in disease.
Strong preference will be given to individuals with a track record of both individual and team contributions in solving complex research problems, and experience in cutting-edge computational methodologies applied to biological -omics, spatial, pathological, and/or clinical metadata.
At the Allen Institute, we believe that science is for everyone – and should be open to everyone. We are dedicated to combating biases and reducing barriers to STEM careers more broadly.
We also believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment.
We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions.
Essential Functions

Develop modern machine learning algorithms to model disease progression from multimodal data (omics, neuropathology, MRI, genetic information, clinical histories)
Develop Bayesian statistical models of neurodegenerative progression
Evaluate models that can harmonize multiple cohort information
Develop causal models of disease progression
Stay at the forefront of advances in AI for multimodal disease progression modeling
Participate in a highly interactive and multidisciplinary environment
Publish/present findings in peer-reviewed journals/scientific conferences
Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects management’s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.
Required Education And Experience

Ph.D. in Computer Science, Applied Math, Engineering, Computational Neuroscience, Computational Biology, or related field, or equivalent combination of degree and experience
Experience working with recent Deep Learning Architectures/Foundational Models
Experience with Bayesian modeling and inference
Experience developing causal models
Preferred Education And Experience

Experience with current ML models such as score-based diffusion models, multimodal data fusion transformer architectures, or state-space models.
Proficiency with cloud computing and with on-prem clusters
Strong publication track record
Proven ability to work independently and manage multiple projects simultaneously while meeting deadlines in a highly collaborative environment
Excellent written and verbal communication skills, with the ability to collaborate effectively in a multidisciplinary team environment.
Physical Demands

Occasional lifting up to 30 pounds (reference: a ream of paper weighs approx. 5lbs
Fine motor movements in fingers/hands to operate computers and other office equipment; repetitive motion with lab equipment.
Position Type/Expected Hours of Work

This role is currently able to work both remotely and onsite in a hybrid work environment. We are a Washington State employer, and the primary work location for all Allen Institute employees is 615 Westlake Ave N.; any remote work must be performed in Washington State.
Travel

Occasional attendance and participation in national and international conferences
Additional Comments

**Please note, this opportunity offers relocation assistance**
**Please note, this opportunity may offer visa sponsorship**
Annualized Salary Range
$92,250 - $114,100 *

Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable.
Benefits
Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute’s Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institute’s 401k plan. Paid time off is also available as outlined in the Allen Institutes Benefits Guide. Details on the Allen Institute’s benefits offering are located at the following link to the Benefits Guide: https://alleninstitute.org/careers/benefits .
It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.