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Design and implement novel machine learning models for RNA structure prediction and drug targeting.Assess and enhance the capabilities of our structure prediction platform.Collaborate with our wet lab team to strategically gather experimental data that refines our machine learning models.Write high-quality code in a collaborative environment.Contribute to the continuous advancement of our machine learning methodologies.
About the job
At Atomic AI, we are at the forefront of innovation, utilizing artificial intelligence to revolutionize drug discovery. Our cutting-edge R&D platform, highlighted on the cover of Science, aims to tackle previously undruggable diseases through RNA targeting. We are continuously enhancing our platform by developing advanced machine learning techniques and unique foundational models, driven by our extensive in-house experimental data collection. Our diverse team of scientists and engineers is the cornerstone of our success.
About the Role
As a full-time Machine Learning Scientist, you will collaborate with engineers and experimental scientists to propel our technology platform for RNA structure prediction, target identification, and early drug discovery. You will co-lead the development and assessment of our machine learning pipeline, bringing innovative ideas to fruition within our continuously evolving state-of-the-art platform. Your proactive contributions will help shape the machine learning strategies and overall vision of the company.
About Atomic AI
Atomic AI is pioneering a new era in drug discovery through the application of artificial intelligence. Our unique approach combines state-of-the-art techniques with a dedicated team of experts, committed to finding innovative solutions for challenging health issues. Join us as we strive to transform the landscape of medicine.
Machine Learning Scientist
Atomic AISouth San Francisco, California, United States
Clicking Apply Now takes you to AutoApply where you can tailor your resume and apply.
Unlock Your Potential
Generate Job-Optimized Resume
One Click And Our AI Optimizes Your Resume to Match The Job Description.
Is Your Resume Optimized For This Role?
Find Out If You're Highlighting The Right Skills And Fix What's Missing
Experience Level
Experience
Qualifications
Design and implement novel machine learning models for RNA structure prediction and drug targeting.Assess and enhance the capabilities of our structure prediction platform.Collaborate with our wet lab team to strategically gather experimental data that refines our machine learning models.Write high-quality code in a collaborative environment.Contribute to the continuous advancement of our machine learning methodologies.
About the job
At Atomic AI, we are at the forefront of innovation, utilizing artificial intelligence to revolutionize drug discovery. Our cutting-edge R&D platform, highlighted on the cover of Science, aims to tackle previously undruggable diseases through RNA targeting. We are continuously enhancing our platform by developing advanced machine learning techniques and unique foundational models, driven by our extensive in-house experimental data collection. Our diverse team of scientists and engineers is the cornerstone of our success.
About the Role
As a full-time Machine Learning Scientist, you will collaborate with engineers and experimental scientists to propel our technology platform for RNA structure prediction, target identification, and early drug discovery. You will co-lead the development and assessment of our machine learning pipeline, bringing innovative ideas to fruition within our continuously evolving state-of-the-art platform. Your proactive contributions will help shape the machine learning strategies and overall vision of the company.
About Atomic AI
Atomic AI is pioneering a new era in drug discovery through the application of artificial intelligence. Our unique approach combines state-of-the-art techniques with a dedicated team of experts, committed to finding innovative solutions for challenging health issues. Join us as we strive to transform the landscape of medicine.
