Sr. Scientist, Antibody Discovery and Engineering

The Role Moderna is seeking a highly motivated Senior Scientist to join the Antibody Discovery team within Therapeutics Research. Therapeutics Research generates innovative therapeutic concepts and advances them from early scientific idea through First-in-Human studies. The Antibody Discovery team plays a central role in discovering, engineering, and optimizing antibody-based therapeutic molecules that enable new treatment strategies across Moderna's therapeutic pipeline. This Senior Scientist will be a hands-on scientific contributor focused on protein and antibody engineering, with particular emphasis on yeast display-based discovery and optimization. The role will contribute to antibody discovery programs across oncology and autoimmune disease, applying experimental protein engineering from library and construct design through selection, characterization, optimization, and lead identification. The successful candidate will bring strong expertise in antibody/protein engineering, molecular biology, yeast display, library design, and experimental characterization. This individual will work closely with protein design, computational biology, structural biology, antigen design, and project teams to translate design hypotheses and computational outputs into experimentally testable molecules and libraries, and to use experimental data to guide iterative design-build-test-learn cycles. This is a hands-on scientific role for someone who thrives in a fast-paced, innovative, and highly collaborative environment. The Senior Scientist will independently design and execute complex experiments, lead experimental workstreams within discovery programs, contribute to scientific strategy and problem solving, and help advance differentiated antibody-based therapeutics toward lead nomination. Here’s What You’ll Do Contribute to integrated antibody discovery and engineering campaigns, with primary responsibility for experimental protein and antibody engineering workstreams from design and library strategy through selection, characterization, optimization, and lead identification. Design, build, and execute yeast surface display workflows for antibody discovery and engineering, including library design and construction, FACS-based selections, affinity maturation, specificity and cross-reactivity optimization, and multi-parameter lead enrichment. Partner closely with computational protein design, bioinformatics, structural biology, and antigen design teams to translate in silico designs, sequence/structure hypotheses, and model predictions into experimentally testable constructs or libraries, and to use experimental results to inform subsequent design cycles. Apply molecular biology and protein engineering approaches including cloning, mutagenesis, sequence analysis, construct design, format conversion, expression, and purification across IgG, Fab, scFv, VHH, bispecific/multispecific, T cell engager, TCR engager, CAR-related, and other therapeutic formats. Characterize engineered candidates using biochemical, biophysical, display-based, and functional assays to assess binding, affinity, specificity, epitope diversity, expression, stability, developability, potency, and mechanism of action as appropriate. Analyze yeast-display selection data, sequence and NGS datasets, and orthogonal characterization data to identify structure-function relationships, nominate follow-up variants, and support data-driven lead selection. Independently formulate hypotheses, design complex experiments, troubleshoot technical challenges, and adapt experimental approaches to address critical program questions and scientific risks. Evaluate and implement new antibody/protein engineering methods, display technologies, and analysis approaches that can strengthen discovery quality, throughput, or molecular optimization. Communicate experimental plans, results, and recommendations clearly to cross-functional scientific teams and contribute to technical reports, project updates, and presentations. Coordinate effectively with internal collaborators and external partners, and provide scientific guidance or mentorship to research associates or junior colleagues as appropriate. Here’s What You’ll Need (Basic Qualifications) PhD in protein engineering, molecular biology, biochemistry, immunology, cancer biology, or a related discipline, with 2+ years of relevant post-PhD industry experience in antibody discovery, protein engineering, antibody engineering, or biologics discovery. Strong hands-on experience with yeast surface display for antibody or protein engineering, including library design/construction, FACS-based screening or selection, affinity maturation, and/or specificity optimization. Strong technical foundation in antibody/protein structure-function relationships and the application of engineering approaches to improve binding, specificity, stability, expression, developability, or molecular format. Demonstrated experience collaborating with computational protein design, bioinformatics, structural biology, or related teams to translate computational/design hypotheses into experimental constructs or libraries and to provide experimental feedback that informs iterative design. Strong molecular biology and protein engineering skills, including cloning, mutagenesis, library construction, sequence analysis, expression construct design, protein/antibody expression, purification, and analytical characterization. Experience analyzing sequence-rich datasets generated from display selections or screening campaigns; familiarity with NGS-based library or repertoire analysis is strongly valued. Experience with antibody/protein characterization methods such as affinity determination, epitope binning, competition assays, specificity profiling, developability assessment, Biacore, Carterra, Octet, ELISA, MSD, flow cytometry, or related technologies. Demonstrated ability to independently design, execute, interpret, and troubleshoot complex experiments and to draw clear conclusions and next steps from multidisciplinary datasets. Experience working effectively across multidisciplinary teams and integrating experimental results with structural, computational, biochemical, and/or functional data. Ability to contribute to multiple projects simultaneously, coordinate experimental priorities and timelines, and communicate scientific risks, tradeoffs, and recommendations to project stakeholders. Excellent analytical, organizational, written, oral, and interpersonal communication skills, with the ability to present complex scientific findings clearly to diverse scientific audiences. Collaborative, proactive, resourceful approach to working in a fast-paced, cross-functional, matrixed research environment. Here’s What You’ll Bring to the Table (Preferred Qualifications) Additional experience with advanced yeast or mammalian display approaches, including focused or combinatorial library design, deep sequencing, multiplexed selections, or high-throughput variant characterization. Experience working in iterative computational/experime