13 proteomics uni jobs at NIST

Applications in Forensic Proteomics

RAP opportunity at National Institute of Standards and Technology     NIST Applications in Forensic Proteomics Location Material Measurement Laboratory, Biomolecular Measurement Division opportunity

Developing bioanalytical foundations for analysis in non-model systems

applications become possible including transcriptomic and proteomic analysis. This project aims to develop and disseminate technological resources for non-model organisms. Specifically this includes

Characterization of Protein-based Allergens

[email protected] 301.975.4026 Melissa Meaney Phillips [email protected] 301.975.4134 Description This research focuses on the utilization of proteomics-based approaches to characterize protein-based

Improving Peptide Identification By Making Use of All Levels of Liquid Chromatography-Tandem Mass Spectrometry Analysis

spectrometry; liquid chromatography; mass spectral library; proteomics; peptide identification Eligibility Citizenship: Open to U.S. citizens Level: Open to Postdoctoral applicants Stipend Base Stipend Travel

Mass Spectrometry Data Analysis

This research opportunity will encompass one or more of the following areas: mass spectrometry data analysis, variability and statistical modeling, and/or proteome informatics. The Associate will work with and

Development of Technologies to Enable Single Molecule Protein Sequencing

240.314.6361 Description Despite the great promise for the field of proteomics, technologies for identifying and quantifying low abundance proteins remain limited. Mass spectrometry (MS) is the most widely used

Benchmarking metaproteomic analytical workflows

. Metagenomics is able to evaluate the presence of different taxa or specific genes while transcriptomics is able to define levels of gene expression, but proteomics seeks to identify and measure the translated

Leveraging Artificial Neural Networks for Enhancing GC and LC-MS Metabolomics Data Interpretation and Integration

capable of interpreting this information and integrating data from other “-omic” platforms such as genomics, transcriptomics, and proteomics. Leveraging artificial neural networks is the linchpin

Algorithms for Compound Identification by Mass Spectrometry

Description The translation of a mass spectrum into a chemical identification is often a very imprecise and error prone part of the rapidly expanding fields of mass spectrometry-based proteomics and

Building and Using Mass Spectral Reference Libraries

materials), advanced algorithms for identification by spectrum matching, and using libraries to measure the reproducibility and reliability of analysis of complex mixtures in metabolomics and proteomics