Role: Scientist, Computational Biology

Adimab is the leading technology provider for therapeutic antibody drug discovery, focusing solely on our partnerships without pursuing an internal product pipeline. Since 2009, we have partnered with over 120 pharmaceutical and biotechnology companies, generating more than 550 therapeutic programs, of which more than 75 have entered clinical trials.

Role Overview
We are seeking a creative individual to join our Computational Biology group located in Mountain View, CA. The ideal candidate is a computational antibody/protein engineer, data scientist, or bioinformatician, with broad-based expertise in one or more of the active project areas within the Computational Biology group. These include protein structure modeling and design, machine learning/deep learning, next-generation sequencing (NGS), or immune repertoire analysis, alongside hands-on experience in scientific programming and cloud computing.

Responsibilities

• Perform data mining on proprietary and public antibody sequence and structure databases to derive insights for antibody library design and selection efforts.
• Develop computational NGS workflows for characterization of antibody libraries and selection outputs.
• Analyze and summarize for non-computational audiences a variety of structure and/or sequence based in silico predictions and experimental data resulting from active antibody discovery campaigns.
• Execute a combination of approaches (machine learning/protein structure modeling and design) for antibody and protein engineering (affinity, specificity, developability, Fc modifications, bispecifics, antigen design).
• Work alongside the Computational Biology team to develop novel computational and machine learning methods to apply to antibody and protein engineering.

Desired upon hire

• Ph.D. in a relevant discipline (Biophysics, Bioinformatics, Biostatistics, Computational Biology, Genetics, Computer Science, or related)
• Three or more years’ experience with peer-reviewed publications in research areas mentioned above in a combined computational/experimental academic lab or industry setting.
• Experience with protein modeling and visualization software (Rosetta, Yasara, PyMol)
• Experience with DNA/RNA-seq platforms and approaches.
• Ability to analyze Next Generation Sequencing datasets.
• Familiarity with both antibody-related and standard genomic and protein databases such as IMGT, OAS, UCSC, NCBI, UniProt, PDB.
• Programming
  • Fluent in Python
  • Ability to integrate tools/modules into custom pipelines.
• Data science and machine learning
  • Demonstrated skills with visualization and collaboration tools such as git, Jupyter notebooks, matplotlib, ggplot2, Plotly, or others.
  • Familiarity with performing and communicating statistical analyses.
  • Expertise with TensorFlow/Pytorch or similar machine learning frameworks preferred.
• Experience applying and adapting relevant foundational models in protein modeling and design to scientific problems, such as structural design diffusion models, LLMs for protein sequences, or others, preferably in a cloud computing environment.

Come join us!
As a profitable privately held biotech company, we take a long-term view on value creation and make substantial investments in technology development, research, and our people. We proudly promote meritocracy and reward employees who are productive, use their resources wisely, and make meaningful contributions to the team. We offer individually tailored compensation packages comprised of a competitive salary, meaningful equity, a 2:1 401(k) match, and comprehensive health care benefits.

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