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using cutting-edge single-cell methods established at the Allen Institute and through the NIH BRAIN Initiative.. The successful candidate will have a strong background in computational biology, and experience developing deep generative models and Bayesian algorithms.. 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.. PhD in computer science, neuroscience, physics, mathematics, engineering, or related field; or an equivalent combination of degree and experience. Experience in computational biology

scientist ii

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Scientist I - ML / AI Algorithms for Alzheimer’s Disease Scientist I – ML / AI Algorithms for Alzheimer’s Disease
The mission of the Allen Institute is to unlock the complexities of bioscience and advance our knowledge to improve human health. Using an open science, multi-scale, team-oriented approach, the Allen Institute focuses on accelerating foundational research, developing standards and models, and cultivating new ideas to make a broad, transformational impact on science.
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.
We have recently begun a major consortium program to understand the cellular and molecular basis of Alzheimer’s disease using cutting-edge single-cell methods established at the Allen Institute and through the NIH BRAIN Initiative. We are mapping Alzheimer’s disease progression by generating unique, large-scale (millions of cells) single nucleus transcriptional, chromatin accessibility, and spatial information, together with detailed neuropathological and cognitive information.
We seek to fill a Scientist-level position to design modern machine learning methods to 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. 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.
This position will work with interdisciplinary teams consisting of quantitative and experimental scientists on high-priority modeling and analysis problems that include (i) statistical descriptions of regulators of cell identity and disease progression, (ii) deep generative modeling-based analysis of multi-modal datasets, and (iii) causal models of disease progression.
The Allen Institute believes that team science significantly benefits from the participation of diverse voices, experiences, and backgrounds. High-quality science can only be produced when it includes different perspectives. We are committed to increasing diversity across every team and encourage people from all backgrounds to apply for this role.
Essential Functions
Develop deep generative models characterizing regulators of cell identity and neurodegenerative progression
Develop novel Bayesian inference algorithms for multi-modal data
Develop causal models of disease progression
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
PhD in computer science, neuroscience, physics, mathematics, engineering, or related field; or an equivalent combination of degree and experience
Experience with Bayesian modeling and inference
Experience working with recent Deep Learning Architectures
Knowledge of Python/R and high-performance computing
Familiarity with analysis of RNA-sequencing or related data types
Preferred Education and Experience
0 - 3 years of directly relevant postdoc work or research experience
Ability to work effectively in a highly collaborative environment
Analysis of single-cell chromatin and transcriptional landscapes
Experience in computational biology
Experience with GPU-based deep learning
Proven independent thinking
Strong written and verbal communication skills
Strong publication record
Physical Demands
Fine motor movements in fingers/hands to operate computers and other office 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 offersrelocation assistance**
**Please note, this opportunity offers work visa sponsorship**
Annualized Salary Range
$80,250 - $115,750 *
* Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable.
Employees (and their families) are eligible to enroll in benefits per eligibility rules outline 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. #J-18808-Ljbffr

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