R&D Summer Internships

* Laboratory experience in handling samples (course-based and/or academic/industry research).
* Good knowledge of biochemistry, analytical chemistry, and/or protein science concepts from college-level coursework.
* A self-motivated individual with a willingness to learn new techniques and computer tools for analysis.
* Coursework or project experience in proteomics, liquid chromatography, mass spectrometry, or protein biochemistry.
* Familiarity with LC-MS/MS platforms or proteomic data analysis software.
* Experience with protein sample preparation techniques such as immunoprecipitation, enzymatic digestion, or chromatographic separations.
* Basic experience in data analysis (Excel, Graph Pad Prism, JMP, Python, or R) will be beneficial.
* Laboratory experience in either an academic or industry setting
* Good knowledge of biochemistry/molecular biology concepts and understanding of techniques in which to test them
* A self-motivated individual with a hunger to learn
* Learn to critically evaluate results and distinguish between technical artifacts and biological signals
* Develop the ability to troubleshoot experimental failures and propose solutions
* Develop confidence in communicating scientific ideas clearly and concisely
* Coursework or project experience in
** protein modeling, docking, or structural analysis
*** Familiarity with
** binding kinetics, or related bioanalytical methods
*** Previous laboratory or research experience in
** antibody engineering, protein engineering, or molecular biology
*** Practical experience with
** molecular modeling and docking
** software platforms
* Knowledge of
** antibody structure, and paratope–epitope interactions.
*** Exposure to
** bioanalytical platforms
** used to characterize binding kinetics and affinity
* Skills in
** experimental planning, documentation, and data interpretation
*** Experience translating scientific findings into clear summaries for varied audiences
* Insight into
** R&D workflows**, collaborative research practices, and systematic problem‑solving approaches
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