Mass Spectrometry Scientist / Postdoctoral Researcher – Zhou Lab

Buck Institute•Novato, CA

3d•$75,920 - $85,500•Onsite

About The Position

The laboratory of Dr. Kai Zhou at the Buck Institute for Research on Aging seeks a hands-on mass spectrometry scientist or postdoctoral researcher to establish and operate a structural mass spectrometry platform. The lab investigates how protein structure, interactions, and assembly change with aging and disease, including work on intrinsically disordered proteins, protein complexes, and ribosomes. The successful candidate will take substantial ownership of instrument operation, method development, data quality, and biological interpretation. The role includes establishing structural-MS workflows, developing methods for characterizing proteins and complexes, and building reproducible approaches to increase sample throughput. The candidate will work with protein biochemists, structural biologists, and computational researchers, contribute to experimental design and training, and support publications and consortium deliverables.

Requirements

PhD in analytical chemistry, biochemistry, biophysics, structural biology, or a related discipline. Experienced master’s-level applicants with substantial independent instrument-operation and method-development experience may be considered for an appropriate staff appointment.
Demonstrated hands-on operation of a high-resolution mass spectrometer, including acquisition-method setup, performance assessment, and troubleshooting.
Substantial practical expertise in at least one of the following: native MS, crosslinking MS, HDX-MS, or intact-protein/top-down MS.
Experience connecting sample preparation, acquisition settings, data analysis, and experimental controls to reliable conclusions.
Strong scientific reasoning, careful documentation, and the ability to work independently and collaboratively.

Nice To Haves

Native electrospray, native MS, intact-protein/top-down or complex-down analysis, or multistage fragmentation.
Crosslinker selection, reaction optimization, enrichment, crosslinked-peptide identification, and false-discovery-rate assessment.
Recombinant protein purification, sample-integrity assessment, and troubleshooting aggregation or heterogeneity.
Analysis of disordered proteins, heterogeneous assemblies, or ribonucleoprotein complexes.
Workflow automation, quantitative analysis, or scripting for reproducible data processing; familiarity with crosslinking or proteoform-analysis software.
Experience supporting complementary bottom-up proteomics or metabolomics applications.

Responsibilities

Establish, optimize, and run structural-MS workflows, including low-flow LC for bottom-up proteomics and crosslinking, and a separate LC workflow for intact-protein and native MS analysis.
Develop native-MS and/or crosslinking-MS methods to characterize protein-complex composition, stoichiometry, interactions, and structural changes; explore intact-complex and complex-down MS workflows where experimentally feasible.
Prepare and evaluate samples through buffer exchange, desalting, crosslinking, digestion, and enrichment as appropriate; optimize native SEC or rapid online buffer exchange while assessing sample integrity and complex stability.
Optimize ionization, ion transmission, precursor isolation, and fragmentation for heterogeneous proteins and assemblies.
Assess instrument performance, troubleshoot problems, and coordinate maintenance and training with vendor specialists.
Establish quality-control standards, reproducible protocols, and reliable workflows for increasing sample throughput, including automated or unattended acquisition, batch QC, carryover checks, and reproducible switching between native and denaturing analyses.
Analyze and interpret spectra with appropriate controls, uncertainty assessment, and validation; distinguish solution-state interactions from source-induced dissociation or adducts and assess crosslink identifications and proteoform/PTM assignments as appropriate.
Maintain clear experimental records and organize raw data, analysis files, and protocols.
Collaborate on experimental design, train colleagues, and contribute to publications and consortium deliverables.