Associate Scientist, Proteomics

Website BioNTech_Group BioNTech US

BioNTech is seeking a highly motivated Associate Scientist to join our Proteomics team. The successful candidate will work independently and as part of a team to help develop, implement and apply state of the art proteomics technologies for the detection, identification and quantification of naturally processed and presented peptide antigens across oncology and infectious disease programs.  The candidate will be part of a cross-functional team made up of immunologists, biochemists, clinicians and computational biologists whose goal is to design and contribute to novel immunotherapies.


Sample preparation for nanoLC-MS/MS analysis, including desalting, chemical modification, fractionation, and isobaric tag labeling
Optimization and execution of immunopurification and other enrichment strategies
Method development and implementation of protein purification strategies for isolation of membrane and intracellular proteins from cells and tissues
Participate in cell culture and sample generation
Instrument maintenance (Thermo and Bruker instruments)
nanoLC-MS/MS analyses of biologically derived protein and peptide mixtures
Analysis of nanoLC-MS/MS data and post-processing of data
Contributions to nanoLC-MS/MS experimental design
Review of scientific literature and collaboration with cross-functional teams
Tracking and compiling of results in an electronic notebook
Assisting with training of lab personnel
Presentation of results to cross-functional teams


MS degree or equivalent industry experience in proteomics, mass spectrometry, biochemistry, and/or analytical chemistry
Background in biochemistry, cell biology, molecular biology, biotechnology and immunology
Strong familiarity with proteomic workflows for sample processing (enzymatic digestion of proteins, chemical modification of peptides such as iTRAQ/TMT, desalting, fractionation, isobaric tag labeling, etc.) and ability to troubleshoot/modify such protocols.
Familiarity with nanoLC-MS/MS workflows for data acquisition including unbiased (e.g. DDA, DIA) and targeted (e.g. PRM, IS-PRM) data collection and MS-based quantitative assays, and ability to modify such methods


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