Senior Scientist, Machine Learning

San Francisco Bay Area, CA

Altos Labs

Altos Labs is a biotechnology company focused on restoring cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that occur throughout life. Learn more about Altos.

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Our Mission

Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.

For more information, see our website at altoslabs.com.

Our Value

Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission.

Diversity at Altos

We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.

Altos Labs aims to foster scientific creativity, providing research labs with both resources and freedom needed to pursue fundamental scientific challenges, including the ability of individual labs to publish and present their work for wider scientific community.

The Kharchenko lab at Altos Labs San Diego Institute is studying how cells coordinate their activity within complex biological tissues, how these mechanisms break down in disease and injury, and the potential interventions that may improve tissue function. Much of the effort is focused on development and application of novel computational tools for understanding tissue function, including analysis of multi-omics and spatial assays where techniques of compute vision and deep learning are highly pertinent.

What You Will Contribute To Altos

Scientist will be expected to lead development and application of computational methods for analysis of spatial omics data together with more traditional microscopy images, in the context of biological studies of different diseases, aging and other processes impacting tissue homeostasis. Particular emphasis will be placed on analysis of tissue architectures, deciphering cell communications, and control of proliferation within tissues. Successful candidate will collaborate with both internal and external experimental groups, lead or participate in planning experimental designs, author and contribute to biological and methodological manuscripts, contribute to seminars and other scientific initiations within Altos as well as wider scientific community.

Who You Are

Minimum Qualifications

  • Expert knowledge deep learning methods and computer vision
  • Experience in developing tools in python, including modern machine learning frameworks (TensorFlow, PyTorch, JAX)
  • PhD. in Computer Science or a related discipline
  • Experience working at the intersection of computation and biology
  • Track record publications in peer-reviewed journals or conferences
  • An interest in carrying out genomics research in collaborative settings

Preferred Qualifications

  • Experience in analysis of microscopy or spatial omics data
  • Expertise in a large subset of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
  • Expertise in computational infrastructure for deep learning including GPUs, TPUs, cloud based machine learning
  • Working knowledge of R
  • Experience in developing tools in python, including modern machine learning frameworks (TensorFlow, PyTorch, JAX)
  • Familiarity with multi-omic integration or spatial transcriptomics analysis

The salary range for Redwood City, CA

  • Scientist I, Machine Learning: $200,600 - $271,400
  • Scientist II, Machine Learning: $236,000 - $330,000
  • Senior Scientist I, Machine Learning: $275,000 - $384,000

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What We Want You To Know

We are a culture of collaboration and scientific excellence, and we believe in the values of inclusion and belonging to inspire innovation.

Altos Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. 

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. 

Altos currently requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions (e.g., due to a medical condition or sincerely-held religious belief).

Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.

Note: Altos Labs will not ask you to download a messaging app for an interview or outlay your own money to get started as an employee. If this sounds like your interaction with people claiming to be with Altos, it is not legitimate and has nothing to do with Altos. Learn more about a common job scam at https://www.linkedin.com/pulse/how-spot-avoid-online-job-scams-biron-clark/

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Tags: Architecture Bayesian Biology Computer Science Computer Vision Deep Learning Generative modeling JAX Machine Learning ML models PhD Privacy Python PyTorch R Reinforcement Learning Research TensorFlow

Perks/benefits: Career development Conferences

Region: North America
Country: United States

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