[ AI Scientist Job Description ]
Join our innovative biotech startup focused on leveraging artificial intelligence to accelerate drug discovery and development. We're seeking a highly motivated and skilled AI Scientist to design, implement, and deploy cutting-edge machine learning and deep learning models on complex biological data.

[ Key Responsibilities ]
The AI Scientist will be a core member of our interdisciplinary team, responsible for:
• Model Development: Design, train, optimize, and validate machine learning (ML) and deep learning (DL) models for tasks such as predicting drug-target interactions, analyzing genomics/proteomics data, virtual screening of compounds, and modeling biological pathways.
• Algorithm Research: Stay abreast of the latest advancements in AI/ML research and apply novel algorithms to solve challenging problems unique to the biotech domain.
• Pipeline Implementation: Develop scalable and reproducible computational pipelines for model training, evaluation, and deployment within our cloud infrastructure.
• Collaboration: Work closely with biologists, bioinformaticians and other AI scientists to translate biological questions into measurable AI problems and integrate AI solutions into the discovery process.
• Communication: Clearly communicate complex results, model limitations, and insights to both technical and non-technical stakeholders.

[Job Summary]
We are looking for a versatile, mid-level Bioinformatician to join our growing team. This is a high-impact role where you will directly influence our drug discovery pipeline by transforming raw wet-lab screening data into therapeutic leads. As an early member of the computational team in a startup environment, you will be a "full-stack" contributor—responsible for both the technical execution of NGS pipelines and the strategic interpretation of emerging biotech trends.

[Key Responsibilities]
• NGS Data Execution: Execute and refine pipelines to process high-throughput sequencing data from various display platforms (Phage, Yeast, or B-cell screening).
• Candidate Discovery & Ranking: Identify and prioritize antibody leads by analyzing clonal enrichment, sequence diversity, and predicted "developability" (e.g., avoiding aggregation or immunogenicity).
• Cross-Functional Collaboration: Act as the primary bridge between data and the bench. You will partner closely with wet-lab scientists to interpret screening results and provide rapid feedback to iterate on experimental designs.
• Literature & Tech Scouting: Proactively perform literature surveys and technical "benchmarking" to keep the team informed on the latest developments in AI-driven antibody discovery and NGS methodology.
• Pipeline Evolution: Maintain and improve our Python-based codebase, ensuring it is flexible enough to incorporate new algorithms or public datasets as the field evolves.

Positions coming soon.

MOLCURE is not currently accepting internship applications.
Thank you for your interest in our work.

現在、MOLCUREではインターンシップの募集は行っておりません。
当社にご関心をお寄せいただき、ありがとうございます。

MOLCURE is not currently accepting internship applications.
Thank you for your interest in our work.

現在、MOLCUREではインターンシップの募集は行っておりません。
当社にご関心をお寄せいただき、ありがとうございます。

MOLCURE is not currently accepting internship applications. Thank you for your interest in our work.
現在、MOLCUREではインターンシップの募集は行っておりません。 当社にご関心をお寄せいただき、ありがとうございます。