Aaaipress
2025 Postdoctoral Research Associate - AI/machine learning for analytical and fo
Aaaipress, Princeton, New Jersey, us, 08543
Overview
The Skinnider Lab at Princeton University aims to recruit a postdoctoral fellow or more senior researcher to work on projects related to computational analysis of chemical and biochemical datasets. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025 and will remain open until excellent fits are found. The work is computational in nature but involves close interactions with experimental collaborators; many problems are constrained by inherently low-quality or noisy data. Responsibilities
Develop and apply computational approaches to chemical datasets with artificial intelligence/machine learning (AI/ML) as a major focus. Identify small molecules using mass spectrometry data and explore language models to predict undiscovered small molecules likely to be observed by mass spectrometry. Identify emerging illicit drugs (novel psychoactive substances) in seized drug products or clinical samples when relevant to projects. Collaborate with experimentalists to validate predictions and develop user-friendly tools for broad community use. Contribute to data preprocessing and curation in addition to model development and evaluation. Engage in large-scale meta-analyses of mass spectrometric datasets as applicable. Prepare the candidate for a range of future competitive positions in academia or industry involving computational biology/chemistry and drug discovery/design. Demonstrate motivation, independence, and strong written communication skills; provide evidence via at least one first-author publication in one or more of the following areas: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning/computer science. Prepare and submit an application with a CV, cover letter, and contact information for three references; undergo initial screening with potential programming exercises if applicable. Qualifications
PhD (or expected) in computational biology/chemistry, biochemistry, computer science, chemical engineering, forensic science, or related field. Experience in one or more of the following areas demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning/computer science. Strong written communication skills, independence, and motivation for independent research. Term and Location
Term of appointment is based on rank. Postdoctoral positions are typically for one year with potential renewal pending satisfactory performance and continued funding; more senior ranks may have multi-year appointments. The work location is on campus at Princeton University. Application Process
To apply online, please visit the Princeton posting at the following URL and submit a CV and cover letter. The cover letter should highlight 1–3 publications or preprints that best address the requirements. Please also include contact information for three references. Qualified candidates who pass an initial screening may be provided with short programming exercises to assess skills. Only suitable candidates will be contacted. Requisition No: D-25-LPB-00006; PI278107218. Salary and Benefits
Expected Salary Range: $65,000 - $70,000 per year. The University provides a comprehensive benefits program; details are available via the University information page. The University considers factors such as scope and responsibilities, qualifications, experience, education/training, key skills, market conditions, and applicable agreements when extending an offer.
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The Skinnider Lab at Princeton University aims to recruit a postdoctoral fellow or more senior researcher to work on projects related to computational analysis of chemical and biochemical datasets. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025 and will remain open until excellent fits are found. The work is computational in nature but involves close interactions with experimental collaborators; many problems are constrained by inherently low-quality or noisy data. Responsibilities
Develop and apply computational approaches to chemical datasets with artificial intelligence/machine learning (AI/ML) as a major focus. Identify small molecules using mass spectrometry data and explore language models to predict undiscovered small molecules likely to be observed by mass spectrometry. Identify emerging illicit drugs (novel psychoactive substances) in seized drug products or clinical samples when relevant to projects. Collaborate with experimentalists to validate predictions and develop user-friendly tools for broad community use. Contribute to data preprocessing and curation in addition to model development and evaluation. Engage in large-scale meta-analyses of mass spectrometric datasets as applicable. Prepare the candidate for a range of future competitive positions in academia or industry involving computational biology/chemistry and drug discovery/design. Demonstrate motivation, independence, and strong written communication skills; provide evidence via at least one first-author publication in one or more of the following areas: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning/computer science. Prepare and submit an application with a CV, cover letter, and contact information for three references; undergo initial screening with potential programming exercises if applicable. Qualifications
PhD (or expected) in computational biology/chemistry, biochemistry, computer science, chemical engineering, forensic science, or related field. Experience in one or more of the following areas demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning/computer science. Strong written communication skills, independence, and motivation for independent research. Term and Location
Term of appointment is based on rank. Postdoctoral positions are typically for one year with potential renewal pending satisfactory performance and continued funding; more senior ranks may have multi-year appointments. The work location is on campus at Princeton University. Application Process
To apply online, please visit the Princeton posting at the following URL and submit a CV and cover letter. The cover letter should highlight 1–3 publications or preprints that best address the requirements. Please also include contact information for three references. Qualified candidates who pass an initial screening may be provided with short programming exercises to assess skills. Only suitable candidates will be contacted. Requisition No: D-25-LPB-00006; PI278107218. Salary and Benefits
Expected Salary Range: $65,000 - $70,000 per year. The University provides a comprehensive benefits program; details are available via the University information page. The University considers factors such as scope and responsibilities, qualifications, experience, education/training, key skills, market conditions, and applicable agreements when extending an offer.
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