Pancreatic ductal adenocarcinoma (PDAC) is a highly heterogeneous disease with tumors broadly classified into classical and basal-like molecular subtypes, which differ in biology, prognosis, and therapeutic response. Currently, molecular subtyping relies on tumor tissue RNA profiling, but obtaining sufficient tumor biopsies in PDAC is often challenging.
Emerging technologies such as liquid biopsy-based transcriptomic profiling and artificial intelligence (AI) driven histopathology analysis offer the potential to infer tumor biology using minimally invasive or routinely collected samples. This project will explore whether plasma gene expression signatures and AI-derived features from H&E tumor images can recapitulate PDAC molecular subtypes defined by tumor gene expression.
location: Cambridge, Massachusetts
job type: Contract
salary: $19 - 29 per hour
work hours: 9 to 5
education: Bachelors
responsibilities:
Objectives: The intern will investigate whether non-invasive and digital pathology approaches can identify PDAC molecular subtypes by:
- Evaluating plasma gene expression signatures associated with PDAC molecular subtypes.
- Assessing concordance between plasma transcriptomic profiles and tumor gene expression data.
- Exploring AI-based models trained on H&E pathology images to classify PDAC subtypes.
- Examining whether integrating plasma transcriptomics and AI-derived histopathology features improves subtype prediction.
- Processing and analyzing tumor and plasma gene expression data to identify subtype-associated signatures.
- Comparing plasma-derived signatures with tumor RNA expression profiles to determine concordance.
- Evaluating performance of AI-based histopathology models (already developed internally) in predicting PDAC subtypes.
- Integrating multi-modal data (plasma transcriptomics and digital pathology) to assess predictive accuracy.
- Have developed experience in working with different technologies
- Identify plasma-based gene expression patterns associated with PDAC molecular subtypes.
- Assess the alignment between plasma and tumor gene expression signatures.
- Evaluate the potential of AI-driven H&E analysis for subtype classification.
- Present findings in a summary report and internal presentation, highlighting opportunities for further translational research.
qualifications:
Required:
- Pursuing a Bachelor's or Master's degree in life sciences with a minimum GPA of 3.3
- Must have an interest in learning, biology and AI
- Must have an interest in pursuing a career in Life Sciences/Biotech/Pharmaceuticals
- Ability to manage workload effectively including planning, organizing, prioritizing, and meeting deadlines
- Candidates who are seeking a degree in Biology or have completed Biology coursework
skills: Biology
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.
At Randstad, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.
Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).
This posting is open for thirty (30) days.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
