Princeton University - Princeton, NJ

posted 5 months ago

Full-time - Entry Level
Princeton, NJ
Educational Services

About the position

The Skinnider Lab of the Ludwig Princeton Branch at Princeton University is seeking to recruit a postdoctoral or more senior research associate to engage in innovative projects focused on the identification of illicit drugs through computational mass spectrometry. This position is available starting in March 2024 and will remain open until the right candidates are found. The successful candidates will be responsible for developing and applying computational methodologies to analyze mass spectrometry data, with a significant emphasis on artificial intelligence and machine learning (AI/ML). Candidates will have the opportunity to lead and contribute to a variety of exciting projects, such as the re-analysis of extensive clinical datasets to discover new illicit drugs or collaborating with anti-doping programs to identify novel performance-enhancing substances. The work will build upon recent publications from the lab, including studies on predicting future illicit drugs using chemical language models and re-analyzing large-scale clinical datasets for illicit drug identification. Although the research is primarily computational, it will involve close collaboration with experimental and clinical partners, providing a well-rounded experience in both computational and practical aspects of drug identification. This position is designed to prepare candidates for competitive roles in academia or industry that focus on computational biology and chemistry, machine learning applications in biological data, drug discovery and design, toxicology, or forensic science. Mentorship is a key component of this role, and every effort will be made to support the candidate in achieving their career goals. The ideal candidate will be self-motivated, independent, and possess strong written communication skills. Candidates must demonstrate experience in one or more relevant fields through at least one first-author publication, including computational biology, cheminformatics, analytical chemistry, machine learning, or toxicology. The term of appointment will depend on the rank, with postdoctoral positions typically lasting one year with the possibility of renewal based on performance and funding availability. More senior hires may receive multi-year appointments. To apply, candidates should submit their CV and a cover letter that highlights 1-3 relevant publications or preprints. Additionally, contact information for three references is required. Qualified candidates who pass an initial screening may be asked to complete short programming exercises to evaluate their skills. Only suitable candidates will be contacted, and this position is subject to Princeton University's background check policy. The work will be conducted in-person on the Princeton University campus.

Responsibilities

  • Develop and apply computational approaches for mass spectrometry data analysis.
  • Lead and contribute to projects identifying new illicit drugs through re-analysis of clinical datasets.
  • Collaborate with anti-doping programs to identify novel performance-enhancing drugs.
  • Engage in close interactions with experimental and clinical collaborators.
  • Prepare for competitive positions in academia or industry related to computational biology, drug discovery, and forensic science.

Requirements

  • PhD in computational biology, chemistry, biochemistry, computer science, biological engineering, toxicology, or a related field.
  • Experience in computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, machine learning/computer science, or toxicology/forensic chemistry as demonstrated through at least one first-author publication.
  • Strong written communication skills.
  • Motivated and independent work ethic.

Nice-to-haves

  • Experience with AI/machine learning techniques in drug identification.
  • Familiarity with large-scale clinical datasets.
  • Background in toxicology or forensic science.

Benefits

  • Mentorship opportunities to support career development.
  • Access to collaborative research environment at a prestigious institution.
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