Craifについて

人々が天寿を全うする社会の実現 —— がんという人類最大の課題から、医療の未来を変える

Craifは、2018年に創業した名古屋大学発のバイオAIスタートアップです。「人々が天寿を全うする社会の実現」を掲げ、がんをはじめとする病によって人生の可能性が失われることのない未来を創ろうとしています。がんは、日本では2人に1人が罹患するといわれ、4000年もの間、人類が克服できていない最も大きな課題のひとつです。一方で、がん検診の受診率は40%前後にとどまり、多くの人が早期発見の機会を逃しているのが現状です。誰もが検診の重要性を頭では理解していても、日々の忙しさや「病気は治療するもの」という意識の根強さから、行動にはなかなかつながりません。
Craifは、こうした心理的・社会的なハードルをテクノロジーで乗り越え、誰もが自然に予防・早期発見へと行動できる社会の実現に向けた根本的な課題解決に挑んでいます。

参考資料
■メンバーインタビュー note / 代表小野瀨 note

■会社紹介動画（1:35) / 研究所・検査センター紹介動画（6:18）

■VC X&KSK本田圭佑さん×代表小野瀨対談（7:32）

■YouTubeチャンネル スタートアップ酒場（22:50）

About Craif

Realizing a society where people can live out their natural lifespan — changing the future of medicine, starting with cancer, humanity’s greatest challenge.

Craif is a Bio-AI startup founded in 2018, originating from Nagoya University. Under the mission of “realizing a society where people can live out their natural lifespan,” the company aims to create a future where lives are no longer cut short by diseases like cancer. In Japan, it’s said that 1 in 2 people will develop cancer — a challenge humanity has been unable to overcome for over 4,000 years. Meanwhile, cancer screening rates remain around 40%, meaning many people miss the chance for early detection.

Craif is using technology to overcome these psychological and social barriers, tackling the fundamental challenge of creating a society where everyone can naturally take steps toward prevention and early detection.

Recruitment Background & Career Path

Advanced data science expertise spanning both machine learning and biology is essential for improving the accuracy of testing systems like miSignal and developing new methods. As the business expands, there is an urgent need to strengthen the team with people who can handle everything from model development to operational automation and advancement. This position seeks someone who can lead omics data analysis and new test system development, driving the creation of clinically valuable models.

In the future, this role can grow into a core R&D career involving architecture design for the entire ML pipeline and planning of new tests.

Job Description

Japanese is not required for this position. The entire Analytics team operates in English.

Test System Development & Updates

• Research design
• Analyzing biomolecular data (miRNA, etc.) obtained using Craif’s technology for disease differentiation, biomarker selection, and other medical applications
• Publishing research results through academic papers and conference presentations
• Building machine learning models
• Setting quality standards and accuracy controls
• Designing and conducting analytical and clinical validation of test systems

ML Pipeline Automation & Advancement

• Collaborating with ML engineers and software engineers to automate the cycle from model development to deployment

New Method Development

• Developing new methods for biomarker-based test systems

Required Qualifications (Must-Have)

• Japanese NOT required
• English proficiency sufficient to work in an international team
• Proficiency in at least one programming language (R, Python, Go, C++)
• Experience in analyzing omics data, preferably RNA expression data
• Foundational understanding of probability theory and statistics
• Foundational understanding of statistical machine learning and pattern recognition
• Experience developing ML models using frameworks such as scikit-learn, Keras, TensorFlow, PyTorch (especially supervised learning for classification problems)
• Research or analysis experience in biology or related fields

Preferred Qualifications (Nice-to-Have)

Basic Japanese language skills for casual communication with other team members.

Development Tools

• Docker
• Workflow management languages (Snakemake/Nextflow)
• AWS cloud

ML Experience

• Training on small-size datasets
• Handling imbalanced data

Related Domain Knowledge / Experience

• Transcriptome analysis experience
• Liquid biopsy knowledge/experience
• microRNA knowledge
• cfDNA knowledge
• Foundational understanding of next-generation sequencing and quantitative PCR
• Biological research/analysis experience
• Wet lab experiment experience
• Cancer biology/medical knowledge or analysis experience
• Molecular diagnostics domain knowledge
• Clinical application of machine learning knowledge/experience

Ideal Candidate Profile

The ideal candidate is someone who strongly aligns with the company’s mission and is proactive and undaunted by the unknown. They demonstrate leadership — thinking independently, involving others, and driving projects forward. They enjoy working in teams and producing results while respecting diversity, focusing on what truly matters regardless of age or title. They are motivated to solve social issues, possess strong hypothesis-building and abstract thinking skills, and are quick to test and validate ideas.

※We will carefully review your application and contact you only if we believe we can offer you a suitable position. If you do not hear from us within 10 business days, please understand that we were unable to find a suitable opportunity for you at this time.