Senior Researcher - Application of Machine Learning -3620

Research Title: Application of Machine Learning for the Prediction of Infrared and Mass Spectra of PFAS Compounds (Senior Researcher)  PREP0003620

The work will entail: 

• Developing novel machine learning algorithms for the prediction of physical and chemical properties, infrared and mass spectra, and ionization cross sections using data derived from experiment and computation.
• Implementing algorithms to study the performance of AI/ML classification models.
• Assessing uncertainty in prediction and classification of experimental data as well as data sets derived from quantum chemistry and physics calculations and simulations.
• Computationally testing mathematical and machine learning models with respect to accuracy and uncertainty quantification.
• Developing software to implement the goals stated above (most likely in Python).
• Disseminating results through posters/seminars at international meetings and university seminars.
• Ensuring that all results, findings, data, software, etc. are correctly archived and transmitted through appropriate channels.

Key responsibilities will include but are not limited to:

• Algorithm development, implementation and analysis.
• Analyze heterogeneous data sources.
• Presenting results at internal meetings, and occasional meetings with external stakeholders.
• Ensuring that results, protocols, software, and documentation have been archived or otherwise transmitted to the larger organization.

Qualifications

• A PhD degree in Chemistry, Physics, Mathematics, Computer Science, Data Science, or a related field.
• 4+ years of relevant experience.
• Significant course work in one or more of chemistry, physics, mathematics, statistics and/or computer science.
• Familiarity with one or more AI/ML software packages. Familiarity with relevant, domain-specific software packages is preferred but not required.
• Ability to program in a modern computational language (e.g. Python).
• Strong oral and written communication skills.

Application format: Please send a cover letter and CV as a single PDF file.

To apply: 

• If you are interested in one of these positions, please send an email with the subject "Job Enquiry PREP0003620" to GUNISTPREP@georgetown.edu, where PREP0003620 is the job number noted above.
• Please send your CV and a short cover letter explaining your suitability for the position.
• Please combine your documents into a single document in PDF format.

For the full job description: https://georgetown.box.com/s/b4xfegx08e7y5r99u4qodibe97lactgv