Juliette D.

Key Skills

Software

Don't disclose

Top Subject Matter

Oncology / liquid biopsy imaging analytics

Immunology / virology sample labeling

Top Data Types

Image

Top Task Types

Classification

Data Collection

Entity (NER) Classification

Freelancer Overview

Summer Research, Convergent Institute for Cancer, USC (cell-matching algorithms & neural network pipeline for CTC detect. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Bachelor of Science in Biochemistry, University of Southern California (2029) and International Baccalaureate Diploma Programme, French International School of Hong Kong (2025). AI-training focus includes data types such as Medical, DICOM, and Image and labeling workflows including Classification, Data Collection,

Labeling Experience

Summer Research, Convergent Institute for Cancer, USC (cell-matching algorithms & neural network pipeline for CTC detection/phenotyping)

Don't discloseClassification

Used fluorescence imaging intensity measurements to support circulating tumor cell detection and phenotyping across a large set of patient blood slides. The work involved building on a two-stage neural network pipeline to analyze how imaging intensity influences model outputs for clinical liquid biopsy optimization. This required preparing and aligning patient slide data for downstream model training and evaluation. • Worked across 103 patient blood slides. • Extended a two-stage neural network pipeline for detection/phenotyping. • Analyzed fluorescence imaging intensity effects on model performance. • Interpreted results in the context of clinical liquid biopsy use cases.

2026 - Present

Research Internship Student - Hong Kong University-Pasteur Research Pole (HKU-PRP)

ImageEntity (NER) Classification

Two-week research internship supporting studies of influenza immune responses in collaboration with HKU graduates. Performed immunological assays to measure viral titers for H1N1 strains and supported lab process improvements. Applied foundational skills in laboratory research practices, sample handling, and data-focused experimental workflows. • Conducted immunological assays for viral titer measurement of H1N1 strains • Optimized sample labeling processes for 500+ patient specimens • Collaborated with research graduates investigating influenza immune responses • Supported consistent lab execution and documentation

2023 - 2023

Internship, Hong Kong University-Pasteur Research Pole (HKU-PRP) (optimized sample labeling for patient specimens)

Don't discloseData Collection

Optimized sample labeling processes for a large cohort of patient specimens during influenza immune response research. The labeling optimization supported reliable assay workflows and downstream analysis of viral titers for H1N1 strains. This work was focused on improving how biological samples were identified and organized for experimental and analytic consistency. • Optimized labeling for 500+ patient specimens. • Supported immunological assays to determine viral titers. • Collaborated with research staff investigating influenza immune responses. • Ensured labeled specimen readiness for subsequent assay and analysis steps.

2023 - 2023

Education

Work History