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Computational Biology and Machine Learning Scientist

Amber Bio
Hayward, CA Full Time
POSTED ON 1/22/2025
AVAILABLE BEFORE 4/22/2025

Amber Bio is at the forefront of biotechnology, innovating new gene editing techniques through multi-kilobase edits aimed at previously challenging patient populations. Established by leaders in the CRISPR field from prestigious research institutions, we are developing a pioneering RNA writing platform capable of correcting thousands of bases simultaneously, thereby providing safe and reversible solutions to genetic mutations. We are expanding our rapidly growing team and have multiple openings available. As an early team member, you will play a crucial role in strategic planning and future hiring. If you aspire to revolutionize genetic medicine, we encourage you to apply.

If you are a dedicated Computational Biologist or ML Scientist with a strong interest in applying machine learning techniques to biological sequence analysis, we invite you to join our dynamic team.

Key Responsibilities :

  • Develop and implement innovative methods to predict RNA and protein function from their sequences.
  • Analyze and preprocess experimental data, including DNA, RNA, protein sequences, high-throughput screening results, and structural data for model training and validation.
  • Design and execute machine learning experiments, setting clear milestones and timelines to meet research objectives.
  • Collaborate closely with wet lab scientists to align machine learning experiments and incorporate model insights into the design processes.
  • Refine models using tailored datasets and external resources to enhance predictive accuracy.
  • Engage with gene editing and molecular biology specialists to integrate modeling insights into practical applications.
  • Stay informed about cutting-edge advancements in machine learning, RNA / protein structure prediction, and gene editing technologies.
  • Publish findings in prominent conferences and peer-reviewed journals.
  • Design, develop, and maintain computational pipelines to process and analyze next-generation sequencing data, including variant calling and differential expression analysis.

Qualifications :

  • Ph.D. in Computer Science, Bioinformatics, Computational Biology, Molecular Biology, or related fields, with a solid foundation in machine learning and molecular biology.
  • At least 2 years of experience in developing machine learning models, particularly in RNA and protein structure prediction, gained through Ph.D. studies or post-doctoral roles.
  • Demonstrated ability to tackle significant biological challenges using statistical and machine learning methodologies.
  • Familiarity with gene editing technologies such as CRISPR-Cas9.
  • Experience utilizing RNA and protein structure prediction tools and databases (e.g., Rosetta, RNAfold, PyRosetta, AlphaFold).
  • Proficient in Python and frameworks like PyTorch or TensorFlow, alongside other bioinformatics tools.
  • Excellent communication abilities and a strong capacity to work collaboratively with both technical and non-technical teams.
  • Strong analytical skills and a creative approach to solving complex molecular problems.
  • Preferred Attributes :

  • A high level of motivation, strong work ethic, and commitment to creating a positive impact.
  • A clear long-term personal vision with defined career objectives.
  • Strong emotional intelligence and a collaborative team mindset.
  • If you are passionate about advancing gene editing technologies and want to be part of an innovative biotech company, we encourage you to apply and join our ambitious team. Amber Bio is an equal-opportunity employer and actively promotes diversity in our workforce. We welcome applications from candidates of all backgrounds and are committed to cultivating an inclusive and supportive work environment.

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