Postdoctoral Research Associate - Computational Mass Spectometry

at  Springer Nature

POSTDOCTORAL RESEARCH ASSOCIATE - COMPUTATIONAL MASS SPECTOMETRY

Employer
Ludwig Princeton Branch, Princeton University
Location
Princeton, New Jersey
Salary
Dependent on experience
Closing date
1 May 2024
Discipline
Biomedicine, Chemistry, Computing, Engineering
Job Type
Postdoctoral, Researcher
Employment - Hours
Full time
Duration
Fixed term
Qualification
PhD
Sector
Academia
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The Skinnider Lab of the Ludwig Princeton Branch at Princeton University aims to recruit one to two postdoctoral associates or more senior research positions to work on projects related to computational analysis of and machine-learning approaches to mass spectrometry-based metabolomics and/or proteomics data. Positions are available starting March 2024, and will remain open until excellent fits are found.
The scope of the work builds on recent publications from the laboratory, e.g. integrating language models with mass spectrometry data (https://www.nature.com/articles/s42256-021-00407-x, https://www.nature.com/articles/s42256-021-00368-1) developing bio- and cheminformatic tools to discover bacterial natural products (https://www.nature.com/articles/s41467-020-19986-1, https://www.nature.com/articles/nchembio.2018), or executing repository-scale meta-analyses of mass spectrometric datasets (https://www.nature.com/articles/s41592-021-01194-4). The research is computational in nature but involves close interactions with experimental collaborators. Many of the problems are constrained by inherently low-quality or noisy data, and the successful candidate will be enthusiastic about contributing to data preprocessing and curation in addition to model development and evaluation.
This opportunity will prepare candidates for a range of competitive positions in academia or industry that involve computational biology/chemistry, machine-learning for biological data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve goals in the next stage of their career. The successful candidate will be motivated, independent, and have strong written communication skills. Candidates are required to have experience in one or more of the following areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning/computer science.
This position is subject to Princeton University’s background check policy. The work location for this position is in-person on campus at Princeton University.

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