Computational Scientist, Machine Learning

What You Will Contribute To Altos

We are looking for a creative and collaborative individual to join our multidisciplinary team of scientists and engineers building the computational and data platforms that will enable Altos to achieve its mission. The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity. As a computational scientist you will help to accelerate and optimize our progress in developing foundation models for multiscale biology.

Responsibilities

• Work on a team of engineers and scientists to train and optimize large-scale machine learning systems using multimodal biological data.
• Develop new statistical and machine learning-based methods applied to biology
• Collaborate closely with experimentalists to design and execute on data collection efforts to be used in computational modeling efforts.
• Continuously learn and stay up-to-date on the latest developments in deep learning for biological discovery.
• Partner with other computational scientists to establish automated, robust, and efficient analytical pipelines for reproducible research.
• Contributes to seminars and other scientific initiatives within Altos and the broader scientific community

Who You Are

Minimum Qualifications

• PhD in Computer Science, Statistics, Machine Learning, or a related discipline
• 0-5 years of relevant work experience in either an academic or industry setting
• Very strong programming skills, including experience with Python and deep learning libraries such as TensorFlow or PyTorch
• Expertise in a subset of the following: transformers, reinforcement learning, graph neural networks
• Proven track record in training and developing machine learning models
• A strong interest in conducting omics-based research in a collaborative setting
• Ability to communicate and explain the design, results, conclusions and the impact of findings to both scientific and nonscientific staff
• Deep analytical thinker and problem solver

Preferred Qualifications

• Track record of ML applied to NGS data, including RNA-seq, ATAC-seq, ChIP-seq, DNA methylation, and others.
• Experience in analysis and processing of spatial transcriptomics data, including integration with imaging-based data modalities (H&E and/or IF).
• Familiarity with multimodal data integration.

The salary range for San Diego, CA:

• Scientist I, Computational Biology: $131,750 - $178,250
• Scientist II, Computational Biology: $155,000 - $214,800

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

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- 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.