BostonGene Technologies

Индустрия: Информационные технологии

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11 Активные вакансии

75 История вакансий

Data scientist (cancer imaging)

Крайний срок: 12 Апрель 2023

Условия контракта: Постоянный

Категория: Программирование

Тип вакансии: Полная ставка

Местонахождение: Ереван

Описание работы

BostonGene is opening a position in Cancer imaging team. You will work with imaging data of different modalities, immunohistochemistry, multiplex fluorescence. Produce statistical analysis, create production ready data pipelines, and integrate it with R&D and clinical systems.

We offer:

The office is located in Yerevan, Armenia, company supports relocation, we provide airplane tickets, hotel accommodation for two weeks, full support in official paperwork, and work permits in Armenia;
Competitive salary and medical insurance;
Full-time position, permanent contract, flexible working hours;
Versatile professional environment: bioinformatics, biologists, physicians, and software developers who united to save people’s lives.

Обязанности

Development of segmentation algorithms for histological images (MxIF, H&E), automated cell classification approach with flexible input features;
Participating in collaborations with leading American hospitals and institutions (Mayo Clinic, Weill Cornell Medicine, NCI, etc); analytics, development of project-specific metrics, annotation team management, presentation of results.
Development of tools for internal needs: cell annotation tool, annotators accuracy dashboard, etc.

Требования

knowledge of python and common data processing and machine learning libraries: numpy, pandas, scipy, scikit-learn;
experience with data visualization using matplotlib, Dash or other libraries;
knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees;
experience with relational databases, knowledge of SQL;
experience with processing of single cell data or spatial transcriptomics data;
experience with deep learning frameworks would be a bonus, pytorch or tensorflow.