Lead Scientist, Cancer Early Detection & Biomarkers

BioSpace; Englewood (NJ); On-site; USD 165,000 - 215,000; Full time

Job summary

ICR seeks a Principal Scientist to lead the Cancer Early Detection Team, focusing on early-stage cancer detection through biomarker arrays and machine-learning-based prediction models. The role involves leading a cutting-edge biomarkers group and driving translatable pan-cancer screening initiatives.

Ideal candidates hold a PhD or MD with 10+ years in cancer research, strong Python programming skills, and deep knowledge of biostatistics and predictive ML methods.

Qualifications

• PhD or MD (or both)
• At least 10 years of cancer research experience, preferably in early detection and biomarkers
• Knowledge of pan-cancer screening, early detection, biomarkers, diagnostics, genetics, prevention and therapeutics
• Programming experience in Python
• Solid grasp of biostatistics and probability theory
• Experience with prediction modeling and machine learning using proper scoring rules

Responsibilities

• Lead a cutting-edge cancer biomarkers group focused on detecting cancer at the earliest stages
• Contribute practical and translatable pan-cancer screening/early detection ideas
• Quantify and track cancer biomarkers (CTCs, cfDNA, serum, plasma, urine proteins, RNA, metabolites, mutations, epigenetics)
• Collaborate with Biomarkers Team on molecular and cellular cancer prevention screening assays in a personalized medicine paradigm

Skills

Python

Biostatistics

Machine learning

Prediction modeling

Education

PhD or MD

Tools

Illumina NextSeq 550

Luminex

Kryptor

Access 2

Tecan

Job description

ICR seeks a Principal Scientist to lead the Cancer Early Detection Team, focusing on early-stage cancer detection through biomarker arrays and machine-learning-based prediction models. The role involves leading a cutting-edge biomarkers group and driving translatable pan-cancer screening initiatives.

Ideal candidates hold a PhD or MD with 10+ years in cancer research, strong Python programming skills, and deep knowledge of biostatistics and predictive ML methods.