Sort by
Refine Your Search
-
at this Level Education/Training: Work requires a PhD degree in biochemistry, molecular biology, pharmacology or other science related scientific field. Experience: None required above education/training
-
or physics Generative AI/transformers, agentic AI, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and Python; best
-
mammalian cells, measurement of biomolecular interactions using Biolayer Interferometry or surface plasmon resonance, structural determination using single-particle cryo-EM analysis, and atomic model building
-
functional genomics Cell and molecular biology Neuroscience or neurobiology Bioinformatics, computational biology, and large-scale data analysis Choose Duke. Successful candidates will join a collaborative and
-
, or computational analysis is considered an advantage. This position is Onsite. The work is performed on-site or at a designated assignment location. Be Bold. Major Responsibilities The successful candidate will
-
, epigenomics, single-cell technologies, stem cell biology, muscle biology, aging, immunology, gene and cell therapy, computational analysis, or animal models are especially encouraged to apply. Strong motivation
-
, molecular biology, pharmacology, and/or a related field. Experience with cell culture, mouse models, and biochemistry/molecular biology is required. Familiarity with gene sequencing techniques/data analysis
-
techniques such as CD, ITC, NMR, EPR, or fluorescence spectroscopy and quantitative analysis. Attributes: A strong publication record, excellent communication skills, and a desire to master new technologies in
-
Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency. 1. A candidate may also be appointed to a postdoctoral
-
across the Duke research community. EDUCATION/TRAINING: PhD in electrical engineering, physics, quantum theory/science, expertise in detection and estimation theory. PREFERRED: Statistical signal