Senior Scientist-Principal Scientist-Antibody Protein Engineering
Listed on 2026-07-17
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Research/Development
Research Scientist, Biotech Research, Biotechnology, Biomedical Science
Full Time
High Throughput Discovery
The heart of Prellis Bio’s strategy is the combination of novel, cutting-edge methods in machine learning, biology at scale, and next-gen antibody discovery that address long-standing industry-wide problems in the drug development pipeline. Prellis Biologics uses proprietary technology to 3D print human lymph node organoids, enabling the rapid & diverse discovery of human antibody therapeutic candidates for a range of applications.
To drive this forward, we are assembling an incredible team of discovery biologists, computational scientists, and protein scientists who want to make a difference to this important problem.
We are seeking a Senior / Principal Scientist — Antibody Protein Engineering to join our High Throughput Discovery group
. You will drive antibody design and optimization, maturing early hits into development-ready leads. You will be responsible for:
- Leading late-stage antibody design and optimization — affinity maturation, Fc engineering, and develop ability polishing to advance lead candidates toward development.
- Building an integrated wet-lab + computational engineering platform — biologics reformatting, multispecific assembly,
screening & library design (high-diversity libraries, focused-library maturation, ML training-data campaigns), and computational design.
The ideal candidate will thrive in a dynamic, hands-on environment and play a critical role in delivering life-changing therapeutics.
Responsibilities- Lead antibody engineering with a strong emphasis on late-stage design and optimization to refine and advance lead candidates toward development. Core activities:
Reformat biologics across modalities (scFv, scFv-Fc, mini bodies, Fab, VHH, Fc fusions, albumin fusions, TCRm) and assemble multispecifics (knob-in-hole, Cross Mab, DVD-Ig, common LC, DARTs) - Fc engineering — mutations for half-life, effector-function modulation, isotype selection, and bispecific heterodimerization
- Affinity maturation — design focused libraries to improve affinity, kinetics, and specificity
- Polishing & develop ability — remove chemical liabilities, mitigate aggregation and immunogenicity, humanize when needed
- Screening & library construction — design and execute campaigns (alanine scanning, high-diversity libraries via PCR, Gibson, mutagenesis, oligo-pool synthesis); generate ML training-data campaigns; translate manual workflows to automation
- Computational design — apply structural tools (PyMOL, Schrödinger Bio Luminate / Maestro) and partner with Data Science / AI/ML on protein language and structure models (Alpha Fold, ESM, RF diffusion, ProteinMPNN, or equivalent)
- Ph.D. in Biochemistry, Bioengineering, Molecular Biology, Protein Engineering, or related field with equivalent industry experience:
Sr. Scientist (PhD + 3-5 yrs);
Principal Scientist (PhD + 5+ yrs) - Hands-on biologics reformatting across scFv, scFv-Fc, Fab, Fc fusions, VHH, and Fc engineering
- Demonstrated experience optimizing / engineering antibody lead candidates (affinity, develop ability, and Fc properties) ands-on experience with biologics screening using iQue and MACSQuantor high content imaging (HCI).
- Computational fluency:
PyMOL, Schrödinger (Bio Luminate / Maestro), molecular dynamics, or equivalent, and at least one protein language model (ESM, RF diffusion, ProteinMPNN, or equivalent) - Strong molecular cloning, mutagenesis, and DNA library construction
- Mentorship of junior researchers; clear scientific communication; track record of publications, presentations, or patents
- Experience managing external vendors (CROs / CDMOs) for biologics production and characterization
- Thrive in cross-functional collaboration
- Strong background in antibody discovery pipelines: expression, purification, screening, and analytical characterization.
- Experience continuous directed evolution (Ortho Rep, PACE): high-diversity libraries (yeast, ribosome, mRNA, mammalian), multi-round selection, and quantitative affinity binning liquid-handling automation (Biomek, Lynx, Tecan), LIMS / ELN (Benchling)
At Prellis we integrate human biology with machine learning. We aim to…
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