Scientist I - ML/AI algorithms for Multimodal Foundational Models

Allen Institute for Brain Science•Seattle, WA

45d•$92,250 - $114,100•Hybrid

About The Position

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 Alzheimers Disease Brain Cell Atlas (SEA-AD) consortium strives to achieve a deep molecular and cellular understanding of the early pathogenesis of Alzheimers 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, infer gene regulatory mechanisms, describe omics trajectories and contribute to the mechanistic understanding of Alzheimers disease pathology. The successful candidate will have a strong background in computational biology, computer science, or statistics, and experience developing and training machine learning models (deep generative models, score-based models, transformer architectures). 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, 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.

Requirements

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 building, deploying and maintaining machine learning and foundational models
Proficiency with cloud computing (AWS, GCP or Azure) and with on-prem clusters
Proven ability to work independently and manage multiple projects simultaneously while meeting deadlines

Nice To Haves

Experience with modeling gene regulatory networks, chromatin accessibility information, or related computational biology studies
Experience building transformer-based foundational models of cell identity
Working knowledge of AI/ML custom libraries, AI/ML execution platforms
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.
Excellent written and verbal communication skills, with the ability to collaborate effectively in a multidisciplinary team environment

Responsibilities

Develop modern machine learning algorithms to model multimodal omics data (transcriptional, chromatin accessibility, genetic, spatial, and protein information)
Evaluate ML architectures able to characterize regulators of cell identity and neurodegenerative progression
Implement sequence-based models to predict genetic contributions to disease
Train large-scale models in multi-GPU environments efficiently
Stay at the forefront of advances in AI for multimodal molecular biology
Participate in a highly interactive and multidisciplinary environment
Publish/present findings in peer-reviewed journals/scientific conferences

Benefits

Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institutes Benefits Guide. These benefits include medical, dental, vision, and basic life insurance.
Employees are also eligible to enroll in the Allen Institutes 401k plan.
Paid time off is also available as outlined in the Allen Institutes Benefits Guide.

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