Associate Scientist, Post Doc Fellow- Quantitative Biosciences Early Discovery

Job Description

Postdoctoral Research Fellow – Quantitative Biosciences Early Discovery

Join the Legacy: Postdoctoral Research Fellowship Program

The company's Research Laboratories Postdoctoral Research Fellow Program is a premier industrial postdoctoral initiative that bridges cutting-edge academic rigor with the world-class resources, technologies, and scientific expertise of a global biopharmaceutical leader. Designed to cultivate the next generation of scientific pioneers, the program empowers postdoctoral investigators to pursue fundamental, high-impact research within an open, collaborative, and innovation-driven environment.

Position Overview:

We are seeking an exceptionally motivated and innovative research scientist for a Postdoctoral Fellowship in the Department of Quantitative Biosciences (QB) Early Discovery at our company's Research Laboratories in Rahway, New Jersey.

In this role, the fellow will pioneer novel drug discovery methodologies in the rapidly expanding field of chemically induced proximity (e.g., molecular glues, heterobifunctional degraders/PROTACs, and proximity-inducing modalities). Leveraging state-of-the-art biophysical, biochemical, structural, and computational platforms, you will collaborate with cross-functional scientific teams to decode complex ternary systems and translate mechanistic insights into drug discovery paradigms.

Fellows are fully supported to author high-impact scientific publications in top-tier peer-reviewed journals, present at premier international conferences, and develop deep expertise in modern industrial early-stage drug discovery.

Responsibilities:

• Lead Research & Innovation: Under the mentorship of senior scientific leaders, conceptualize, design, and execute cutting-edge methodologies to interrogate and exploit chemically induced proximity. Maintain deep familiarity with emerging literature to identify and capture novel therapeutic opportunities.
• Multi-Modal Biophysical & Biochemical Characterization: Integrate quantitative biochemical, biophysical, and structural approaches to investigate macromolecular complexes, ternary complex formation, and protein–small molecule interactions.
• Independent Project Ownership: Formulate and drive an independent research agenda from hypothesis generation to mechanistic validation, working flexibly within multidisciplinary project teams across discovery chemistry, biology, and pharmacology.
• Computational & Experimental Synergy: In close partnership with the Modeling & Informatics team, integrate computational workflows with experimental investigations—curating structural constraints, evaluating predictive protein–ligand and protein-complex models, and prioritizing testable hypotheses.

• Scientific Dissemination: Actively communicate findings through presentations at internal scientific symposia, international conferences, and lead-author publications in peer-reviewed scientific journals.

Education Minimum Requirement:

• Must currently hold a Ph.D. OR
• Receive a Ph.D. no later than spring 2027
• Ph.D. in Biochemistry, Biophysics, Pharmacology, Structural Biology, or related disciplines.

Required Experience and Skills:

• Biophysical & Biochemical Expertise: Demonstrated hands-on expertise in characterizing protein–ligand and protein–protein interactions using quantitative biophysical methods (e.g., SPR, ITC, MST, BLI, or fluorescence-based assays such as TR-FRET/FP).
• Protein Biochemistry: Proven track record in recombinant protein construct design, expression systems, and chromatographic purification (experience with isotopic labeling for NMR or structural applications is highly desirable).
• Biomolecular NMR or Structural Analysis: Working knowledge and practical experience in biological NMR spectroscopy (resonance assignment, chemical shift perturbation, or ligand-observed experiments) and/or structural biology techniques.
• Structural Interpretation: Demonstrated capability to analyze, visualize, and interpret high-resolution protein structures, binding interfaces, and ligand binding modes using molecular modeling software (e.g., PyMOL, MOE, Schrödinger Maestro, or ChimeraX).
• Scientific Track Record: Proven record of scientific productivity and independent thinking, evidenced by first-author publications in reputable peer-reviewed journals and presentations at scientific conferences.
• Collaboration & Communication: Excellent written, verbal, and interpersonal communication skills, with a demonstrated ability to thrive in a highly collaborative, team-oriented research setting.

Preferred Experience and Skills:

• Chemically Induced Proximity & Screening: Prior experience in ternary complex systems, targeted protein degradation (TPD), molecular glues, or early hit-finding platforms (e.g., Fragment-Based Drug Discovery [FBDD], High-Throughput Screening [HTS], or DNA-Encoded Libraries [DEL]).

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