2024 Summer Intern - Machine Learning For Drug Discovery, Prescient Design

Key Skills

Deep Learning, Machine learning techniques, Presentation skills, Python Programming, PyTorch, TensorFlow, Writing

Job Description

Key Responsibilities

• You will participate in cutting-edge research in developing and applying machine learning to predict the structure of small molecules using mass-spectrometry data

• Design, implement, and/or evaluate machine learning models for metabolite enumeration, mass spectra prediction from theoretical metabolites (forward MS), or small-molecule structure prediction from experimental mass-spectrometry data (inverse MS) to contribute towards an improved metabolite ID pipeline for DMPK studies.

• Collaborate closely with machine learning scientists, research engineers, computational biologists, chemists, and biologists

• Report and present research findings and developments including status and results, verbally, and in writing (publishing in top-tier ML venues)

Program Highlights

• Intensive 12-weeks, full time (40 hours per week) paid internship.

• Program start dates are in May or June (Summer)

• A stipend, based on location, will be provided to help alleviate costs associated with the internship.

• Ownership of challenging and impactful business-critical projects.

• Work with some of the most talented people in the biotechnology industry.

Who You Are (Required)

Required Education:

• Must be pursing a PhD focused in the following areas: Computational Biochemistry, Computational Biology, Computational Chemistry, Computer science, Machine Learning or other related field

• Must have completed 1 year of Masters program focused in the following areas: Computational biochemistry/biology, Machine Learning

Required Skills:

• Fluent in Python and experience with modern Python frameworks for deep learning (e.g. PyTorch or TensorFlow)

• Relevant research exposure to deep learning applied to mass spectrometry data analysis for small molecule structure elucidation

• Previous experience in metabolomics research

Preferred Skills:

• Demonstrated computational research experience, as evidenced by publications, public code repositories, or equivalent

• Experience with one or more mass-spectrometry data toolkits (e.g. OpenMS, MZmine, GNPS, Sirius, XCMS)

• Experience working with large chemical and biological datasets

• Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

• Strong collaborative skills, innovative thinking, and a record of problem-solving in complex research environments.

Relocation benefits are not available for this job posting.

The expected salary range for this position based on the primary location of San Francisco, CA is $50/hr. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.