 職種Position |
技術職 (医薬・医療・バイオ)
R&D / Engineer /Technician (Pharmaceuticals, Healthcare, Biotechnology) |
 会社概要Company profile |
■ Company profile
This bio company with a unique high-performance antibody drug development platform makes full use of next-generation sequencing, bioinformatics, and antibody engineering.
By developing high-performance antibody drugs, they have eliminated the inherent bias of conventional methods, created high-performance antibodies that were difficult to obtain until now, and contributed to the development of innovative antibody drugs.
■ Products / Solutions
・ New peptide / antibody drug molecule design technology using evolutionary molecular engineering / NGS / artificial intelligence
・ Construction of joint R & D pipeline with pharmaceutical companies and biotech companies using the above technology (including implementation of molecular design, research plan formulation, consulting)
■ Company profile
This bio company with a unique high-performance antibody drug development platform makes full use of next-generation sequencing, bioinformatics, and antibody engineering.
By developing high-performance antibody drugs, they have eliminated the inherent bias of conventional methods, created high-performance antibodies that were difficult to obtain until now, and contributed to the development of innovative antibody drugs.
■ Products / Solutions
・ New peptide / antibody drug molecule design technology using evolutionary molecular engineering / NGS / artificial intelligence
・ Construction of joint R & D pipeline with pharmaceutical companies and biotech companies using the above technology (including implementation of molecular design, research plan formulation, consulting) |
 仕事内容Job description |
[Job Summary]
We are looking for a Bioinformatics Scientist who will work across the full spectrum of antibody discovery—from mining screening data to computationally designing new candidate sequences. Working at the front line of our antibody discovery engine, you will own the end-to-end NGS analysis pipeline, partner directly with wet-lab scientists to close the loop between computation and experiment, and collaborate with ML engineers to apply generative AI approaches for sequence design and optimization.
This is not a downstream analysis role. You will shape which candidates enter our optimization pipeline—whether discovered from screening data or computationally designed—and your biological interpretation will directly influence lead selection decisions. As an early member of the computational team, you will have the autonomy to define how our discovery informatics evolves.
[Key Responsibilities]
• NGS Pipeline Development & Execution
Build, execute, and continuously refine pipelines for processing high-throughput sequencing data from antibody display and screening campaigns. Ensure reproducibility, scalability, and rapid turnaround to keep pace with experimental cycles.
• Candidate Discovery & Prioritization
Analyze clonal enrichment, sequence diversity, and predicted developability to identify and rank antibody leads. Provide data-driven rationale for which candidates advance to downstream characterization.
• AI-Driven Sequence Design
Collaborate with ML engineers to leverage generative AI and protein language models for de novo antibody sequence design and optimization. Evaluate computationally designed candidates using the same biological and developability criteria applied to screening-derived hits, bridging the gap between generative models and experimental validation.
Wet-Lab Partnership
Serve as the primary computational partner to bench scientists. Interpret screening results collaboratively, provide rapid feedback on experimental outcomes, and co-design iterative screening strategies based on data insights.
• Pipeline & Codebase Evolution
Maintain and improve our Python-based analysis codebase. Architect flexible, modular systems that can incorporate new algorithms, public datasets, and evolving experimental formats as the field advances.
• Scientific Intelligence
Monitor the rapidly evolving landscape of AI-driven antibody discovery and NGS methodology. Evaluate emerging tools and approaches, and bring validated improvements into our production workflows.
[Job Summary]
We are looking for a Bioinformatics Scientist who will work across the full spectrum of antibody discovery—from mining screening data to computationally designing new candidate sequences. Working at the front line of our antibody discovery engine, you will own the end-to-end NGS analysis pipeline, partner directly with wet-lab scientists to close the loop between computation and experiment, and collaborate with ML engineers to apply generative AI approaches for sequence design and optimization.
This is not a downstream analysis role. You will shape which candidates enter our optimization pipeline—whether discovered from screening data or computationally designed—and your biological interpretation will directly influence lead selection decisions. As an early member of the computational team, you will have the autonomy to define how our discovery informatics evolves.
[Key Responsibilities]
• NGS Pipeline Development & Execution
Build, execute, and continuously refine pipelines for processing high-throughput sequencing data from antibody display and screening campaigns. Ensure reproducibility, scalability, and rapid turnaround to keep pace with experimental cycles.
• Candidate Discovery & Prioritization
Analyze clonal enrichment, sequence diversity, and predicted developability to identify and rank antibody leads. Provide data-driven rationale for which candidates advance to downstream characterization.
• AI-Driven Sequence Design
Collaborate with ML engineers to leverage generative AI and protein language models for de novo antibody sequence design and optimization. Evaluate computationally designed candidates using the same biological and developability criteria applied to screening-derived hits, bridging the gap between generative models and experimental validation.
Wet-Lab Partnership
Serve as the primary computational partner to bench scientists. Interpret screening results collaboratively, provide rapid feedback on experimental outcomes, and co-design iterative screening strategies based on data insights.
• Pipeline & Codebase Evolution
Maintain and improve our Python-based analysis codebase. Architect flexible, modular systems that can incorporate new algorithms, public datasets, and evolving experimental formats as the field advances.
• Scientific Intelligence
Monitor the rapidly evolving landscape of AI-driven antibody discovery and NGS methodology. Evaluate emerging tools and approaches, and bring validated improvements into our production workflows. |
 応募資格Requirement |
We need someone who can work across the full arc of discovery informatics—from raw FASTQ files to biological insight. While AI and automation dramatically accelerate throughput, we require a scientist who understands the biology deeply enough to catch what algorithms miss and to know when a computational result demands experimental validation.
[Foundational Expertise (Required)]
• Master’s degree or PhD in Bioinformatics, Computational Biology, Immunology, Molecular Biology, or a related quantitative field.
• 3+ years of hands-on experience in NGS data analysis, with a focus on antibody or immune repertoire sequencing (PhD research counts toward this requirement).
• Strong understanding of antibody biology: V(D)J recombination, clonal selection, affinity maturation, and the sequence-function relationship in antibody engineering. You should be able to assess a candidate’s therapeutic potential from sequence data, not just statistical enrichment.
• Proficiency in Python for bioinformatics workflows. Comfortable building and maintaining reproducible pipelines (e.g., Snakemake, Nextflow), not just running one-off analyses.
• Working familiarity with standard NGS toolchains (e.g., FASTQC, Trimmomatic/Cutadapt, alignment and clustering tools) and biological databases (IMGT, PDB, UniProt).
[ Preferred Qualifications ]
• Experience applying machine learning or statistical methods to sequence analysis tasks—such as enrichment scoring, clustering, or developability prediction—and understanding when these methods add value versus when manual curation is more appropriate.
• Experience using LLM-based AI assistants (e.g., Claude, ChatGPT, GitHub Copilot) or other AI productivity tools to accelerate research workflows—such as code development, literature analysis, data interpretation, or pipeline debugging. We value scientists who actively leverage AI to multiply their output while maintaining scientific rigor.
• Familiarity with protein language models (e.g., ESM-2, AntiBERTy) or antibody-specific computational tools (e.g., ANARCI, AbNum, IgBLAST) is a strong plus.
[Qualities We Value]
- Biological intuition:
You don’t just run pipelines—you interpret results through the lens of antibody biology and can explain why a statistically enriched clone may or may not be a good therapeutic candidate.
- Engineering discipline:
You write clean, documented, testable code. You think about reproducibility and maintainability, not just getting an answer once.
- Intellectual curiosity:
You proactively track new methods in computational immunology and AI for drug discovery, and you bring validated ideas back to the team.
- Startup adaptability:
You thrive in an environment where priorities shift, experimental designs evolve mid-campaign, and you’re expected to figure things out rather than wait for instructions.
We need someone who can work across the full arc of discovery informatics—from raw FASTQ files to biological insight. While AI and automation dramatically accelerate throughput, we require a scientist who understands the biology deeply enough to catch what algorithms miss and to know when a computational result demands experimental validation.
[Foundational Expertise (Required)]
• Master’s degree or PhD in Bioinformatics, Computational Biology, Immunology, Molecular Biology, or a related quantitative field.
• 3+ years of hands-on experience in NGS data analysis, with a focus on antibody or immune repertoire sequencing (PhD research counts toward this requirement).
• Strong understanding of antibody biology: V(D)J recombination, clonal selection, affinity maturation, and the sequence-function relationship in antibody engineering. You should be able to assess a candidate’s therapeutic potential from sequence data, not just statistical enrichment.
• Proficiency in Python for bioinformatics workflows. Comfortable building and maintaining reproducible pipelines (e.g., Snakemake, Nextflow), not just running one-off analyses.
• Working familiarity with standard NGS toolchains (e.g., FASTQC, Trimmomatic/Cutadapt, alignment and clustering tools) and biological databases (IMGT, PDB, UniProt).
[ Preferred Qualifications ]
• Experience applying machine learning or statistical methods to sequence analysis tasks—such as enrichment scoring, clustering, or developability prediction—and understanding when these methods add value versus when manual curation is more appropriate.
• Experience using LLM-based AI assistants (e.g., Claude, ChatGPT, GitHub Copilot) or other AI productivity tools to accelerate research workflows—such as code development, literature analysis, data interpretation, or pipeline debugging. We value scientists who actively leverage AI to multiply their output while maintaining scientific rigor.
• Familiarity with protein language models (e.g., ESM-2, AntiBERTy) or antibody-specific computational tools (e.g., ANARCI, AbNum, IgBLAST) is a strong plus.
[Qualities We Value]
- Biological intuition:
You don’t just run pipelines—you interpret results through the lens of antibody biology and can explain why a statistically enriched clone may or may not be a good therapeutic candidate.
- Engineering discipline:
You write clean, documented, testable code. You think about reproducibility and maintainability, not just getting an answer once.
- Intellectual curiosity:
You proactively track new methods in computational immunology and AI for drug discovery, and you bring validated ideas back to the team.
- Startup adaptability:
You thrive in an environment where priorities shift, experimental designs evolve mid-campaign, and you’re expected to figure things out rather than wait for instructions. |
 日本語力Japanese level |
初級
None |
 雇用形態Employment type |
正社員
Full-time |
 勤務エリアLocation |
フルリモート
Full remote work |
 勤務時間Working hours |
Flexible working hours (discretionary system)
Flexible working hours (discretionary system) |
 想定年収Salary |
¥3M - ¥7M
¥3M - ¥7M |
 条件・待遇Condition |
[ What We Offer ]
• Competitive salary and stock option package in a fast-growing startup.
• Opportunity to make a significant impact on human health and drug development.
• A collaborative, mission-driven, and intellectually stimulating work environment.
[Holidays / Leave]
• Weekends (Saturday and Sunday) and Japanese national holidays
• Paid annual leave: 10 days in the first year (prorated based on the month of joining)
• Refresh leave: 5 days per year
We operate as a fully remote organization, enabling us to recruit the best talent globally. We prioritize flexibility, trust, and output over physical location.
• Global Collaboration: You will be an integral part of a multinational team, collaborating daily with colleagues, partners, and stakeholders across time zones in Europe and Asia.
• Asynchronous Communication: We champion asynchronous communication practices (using tools like Slack, Notion, and email) to ensure deep work periods and accommodate various schedules. Real-time meetings are used judiciously.
• Tool Proficiency: A high degree of comfort and proficiency with digital collaboration tools (e.g., video conferencing, shared code repositories, project management software) is essential for successful remote execution.
• Autonomy & Ownership: This role requires exceptional self-discipline, autonomy, and proactive ownership. You will be expected to manage your schedule, deliver results independently, and contribute actively to team goals without direct daily supervision.
• Cultural Fluency: An appreciation for and sensitivity to diverse cultural backgrounds and communication styles is vital for maintaining a strong, inclusive global team dynamic.
[ What We Offer ]
• Competitive salary and stock option package in a fast-growing startup.
• Opportunity to make a significant impact on human health and drug development.
• A collaborative, mission-driven, and intellectually stimulating work environment.
[Holidays / Leave]
• Weekends (Saturday and Sunday) and Japanese national holidays
• Paid annual leave: 10 days in the first year (prorated based on the month of joining)
• Refresh leave: 5 days per year
We operate as a fully remote organization, enabling us to recruit the best talent globally. We prioritize flexibility, trust, and output over physical location.
• Global Collaboration: You will be an integral part of a multinational team, collaborating daily with colleagues, partners, and stakeholders across time zones in Europe and Asia.
• Asynchronous Communication: We champion asynchronous communication practices (using tools like Slack, Notion, and email) to ensure deep work periods and accommodate various schedules. Real-time meetings are used judiciously.
• Tool Proficiency: A high degree of comfort and proficiency with digital collaboration tools (e.g., video conferencing, shared code repositories, project management software) is essential for successful remote execution.
• Autonomy & Ownership: This role requires exceptional self-discipline, autonomy, and proactive ownership. You will be expected to manage your schedule, deliver results independently, and contribute actively to team goals without direct daily supervision.
• Cultural Fluency: An appreciation for and sensitivity to diverse cultural backgrounds and communication styles is vital for maintaining a strong, inclusive global team dynamic. |
 選考についてProcess |
Documents required for application: Japanese or English resume
Online interview: Available
Interview language: English or Japanese
Number of interviews (flow): 3-4 times
Application for overseas residents: Unavailable
* May change depending on the situation of the candidate
Documents required for application: Japanese or English resume
Online interview: Available
Interview language: English or Japanese
Number of interviews (flow): 3-4 times
Application for overseas residents: Unavailable
* May change depending on the situation of the candidate |
