Career counseling Jobs for Ph.D.
Service
Career counseling
One-on-one career counselingwith a Ph.D. mentorwith academic and/or business experience

Jobs for Ph.D.
You can search for jobs at companies that highly value Ph.D. holders by research or technology keywords.

Settings & Others
Switch Language
Contact
Job Search

Recruit Detail

Find out more about the work we do, the experience and skills we can bring to the table, and our terms and conditions.

Company Name

Preferred Networks, Inc.

Job Type

Drug Discovery Researcher

Work Detail

Preferred Networks (PFN) is seeking researchers for its Drug Discovery division. Computational science in drug discovery is advancing rapidly, with applications progressing in areas such as identifying biomolecules that can be drug targets, predicting their structure and function, and designing, searching for, and optimizing drug candidate molecules (predicting pharmacological activity, toxicity, and kinetics). PFN's Drug Discovery team provides pharmaceutical companies with services that highly integrate cutting-edge technologies, including the P-FEP binding free energy calculation service, with domain knowledge in the drug discovery field. Currently, we are further expanding this proven technological foundation, aiming to build a comprehensive drug discovery platform that consistently covers a wider range of drug discovery processes. Our team is seeking members to develop new technologies that can solve challenges in the drug discovery field. We are seeking professionals who resonate with PFN's mission and values ​​[https://tech.preferred.jp/ja/blog/2025-mission-values/](https://tech.preferred.jp/ja/blog/2025-mission-values/), possess exceptional technical skills to implement cutting-edge theories and "make the real world computable," and have the passion to take initiative (Be Proactive). Team Mission - To contribute to people's health by supporting the creation of innovative medicines using cutting-edge computational science. Job Description - Research and development and commercialization of new technologies in the drug discovery field. - You will be responsible for designing and implementing innovative algorithms that go beyond mere software use. - You will be responsible for various fields, primarily those listed in the application qualifications (required). - Collaborative research with other institutions (pharmaceutical companies, academia, etc.). - Research on the latest research papers and acquisition and implementation of algorithms. - Collaboration with other teams within the company. References - Some of the research and development conducted by PFN to date. - Drug Discovery HP: [https://projects.preferred.jp/drug-discovery/](https://projects.preferred.jp/drug-discovery/) (Content is somewhat outdated) - Technical Blog: [https://tech.preferred.jp/ja/tag/drug-discovery/](https://tech.preferred.jp/ja/tag/drug-discovery/) - Related Keywords - Neural Network Potential - Machine Learning Interatomic Potential - Protein Folding, Structure-aware prediction - ADMET prediction - AI molecular generation - Computational chemistry and molecular simulation - Molecular docking - Molecular dynamics (extended sampling MD, Free Energy Perturbation, etc.) - Structure-based drug design (SBDD) - Ligand-based drug design (LBDD) - Chemoinformatics We are hiring a Researcher to drive Preferred Networks' (PFN) Drug Discovery initiatives. The advancements in computational science in drug discovery have been remarkable, and its applications are expanding across fields ranging from the identification of biomolecular drug targets and the prediction of their structures and functions to the design, exploration, and optimization of drug candidate molecules (including predictions for pharmacological activity, toxicity, and pharmacokinetics). The PFN Drug Discovery team provides pharmaceutical companies with solutions, such as the binding free energy calculation service P-FEP, that integrate advanced computational methodologies with deep domain expertise. We are currently building on these core technologies to create a comprehensive "Drug Discovery Platform" – an end-to-end solution aimed to accelerate a wider range of processes in the drug discovery workflow. We are recruiting a researcher to lead the research and development of novel technologies that address critical challenges in drug discovery. We seek a professional who deeply resonates with our Mission and Values ​​[(https://tech.preferred.jp/ja/blog/2025-mission-values/) ](https://tech.preferred.jp/ja/blog/2025-mission-values/) and possesses the exceptional engineering capability to implement cutting-edge theory into robust software. Team Mission - Contribute to human health by facilitating the creation of innovative medicines using cutting-edge computational science. Responsibilities - Conduct research, development, and productization of new technologies in the drug discovery field - Design and implement innovative algorithms, rather than applying existing software. - Work primarily on the areas specified in the Qualifications, while also handling a variety of other areas - Conduct collaborative research with external institutions - Survey the latest research papers, and master and implement algorithms - Collaborate with other teams within the company Additional Information - Introduction to our research - Drug Discovery HP:[https://projects.preferred.jp/drug-discovery/](https://projects.preferred.jp/drug-discovery/)(old) - Technical Blog:[https://tech.preferred.jp/ja/tag/drug-discovery/](https://tech.preferred.jp/ja/tag/drug-discovery/) - Keywords related to our activities - Neural Network Potential / Machine Learning Interatomic Potential - Protein Folding, Structure-aware prediction - ADMET Prediction - AI-driven Molecular Design - Computational Chemistry, Molecular Simulation -Molecular Docking - Molecular Dynamics (e.g., Enhanced Sampling MD, Free Energy Perturbation) - Structure-Based Drug Design (SBDD) - Ligand-Based Drug Design (LBDD) - Chemoinformatics

Ideal Profile

Qualifications (Required) - Expertise in the field of Drug Discovery (deep knowledge and experience in at least one of the following areas): - Molecular dynamics simulation (high-accuracy activity prediction technologies such as FEP): - Neural Network Potential (NNP) / Machine Learning Interatomic Potential (MLIP): - Protein folding / Structure-aware prediction: - Software development skills: - Ability to independently design and implement complex algorithms and theories using Python, etc.: - Ability to understand computer architecture and implement programs that are mindful of software execution efficiency and computational load: - Experience using and controlling computing resources (GPU/large cluster, etc.) in a Unix/Linux environment: - Expertise and deep experience in at least one of the following areas: - Molecular dynamics simulation (e.g., high-accuracy affinity prediction technologies such as Free energy perturbation): - Neural Network Potential (NNP) / Machine Learning Interatomic Potential (MLIP): - Protein folding or Structure-aware prediction: - Software development skills: - Ability to independently design and implement complex algorithms and Theories using Python - Ability to implement efficient programs with an awareness of computer architecture and computational complexity - Experience utilizing high-performance computing resources in a Unix/Linux environment. Preferred Qualifications - Practical experience in the pharmaceutical or chemical industry (preferably 3+ years) - In-depth knowledge and experience in quantum chemistry, especially for QM/MM calculations - Implementation experience in the field of Machine Learning and Deep Learning (AI)

Work Location

Otemachi Bldg., 1-6-1 Otemachi, Chiyoda-ku, Tokyo, Japan 100-0004 Remote work system available (limited to work in Japan)

Phd. Stating Salary

Compensation will be determined based on experience, performance, abilities, and contributions, in accordance with company regulations.

External Site

https://open.talentio.com/r/1/c/preferred/pages/88382

Similar Recruits

Elix Co., Ltd.

Job Type
Full-stack engineer

Elix Co., Ltd. is an AI drug discovery company with the mission of "rethinking drug discovery." We conduct collaborative research utilizing Elix Discovery™, our cutting-edge AI drug discovery platform, and also provide licenses for the platform itself. Our work primarily covers everything from hit discovery of small molecule compounds to lead optimization. Specific Job Description We are seeking an experienced and enthusiastic full-stack engineer to lead the development of Elix Discovery™ using a user-friendly, maintainable, scalable, and customer-oriented approach. • Engage in all stages of development, from design and implementation to optimization and deployment. • Collaborate with team engineers and researchers to develop practical products for clients. • Support the design and development of highly usable, high-performance, and user-friendly APIs and associated unit tests to ensure code quality. Scope of Changes in Job Description: As defined by the company.

Elix Co., Ltd.

Job Type
Project Leader

Elix Co., Ltd. is an AI drug discovery company with the mission of "rethinking drug discovery." We conduct collaborative research utilizing Elix Discovery™, our AI drug discovery platform that brings together cutting-edge technologies, and also provide licenses for the platform itself. We primarily handle everything from hit discovery of small molecule compounds to lead optimization. Specific Job Responsibilities You will be responsible for supporting and managing the introduction of AI drug discovery projects. You will act as a bridge between clients and internal engineers, managing project progress and execution. • Organizing project requirements and development content, and managing project promotion and execution • Collaborating with internal foreign engineers to create reports and provide performance reports to clients • Introducing research papers and other materials to clients • Creating proposals and introducing our services at exhibitions and academic conferences, etc. Scope of Changes in Job Responsibilities: As defined by the company

Knowledge Palette Co., Ltd.

Job Type
Computational Life Sciences (Machine Learning Engineer/Data Scientist)

In the pharmaceutical industry, where the time and cost of new drug development are increasing year by year, the development of AI technologies such as machine learning and deep learning, and the improvement of computer data processing speed, are expected to play a major role in solving these challenges. In fact, decisive changes such as shortening the drug discovery process and significantly improving the success rate of development are already being brought about. Our company is pursuing a unique approach of "manipulating cells with big data extracted from cells to create new drugs," and is acquiring cellular big data. We are seeking researchers who are motivated by a wide range of research and development, from basic to applied, and who can promote the development of machine learning and data analysis technologies for new drug discovery and the practical application of regenerative medicine. Because we develop cutting-edge experimental and analytical technologies, we can analyze and apply large-scale, high-precision cellular big data that is only possible to acquire at our company. Specifically, in our in-house research and collaborative research, we are developing a wide variety of machine learning algorithms, such as the following: We are looking for someone who can continuously refine and advance these tasks. In addition, we are seeking someone who can proactively propose novel analytical methods using internal and external data, creating new value that leads to the practical application of drugs and regenerative medicine. Depending on aptitude and other factors, you may be assigned to a different role. You may be assigned to a different role depending on your aptitude. Depending on your aptitude, you may be assigned to a different role. Your role may be transferred to a different role as instructed by the company. * Bayesian optimization may be used to optimize cell culture conditions and manufacturing processes for regenerative medicine products. * Bayesian optimization may be used to optimize cell culture conditions and manufacturing processes for regenerative medicine products. Depending on your aptitude and other factors, you may be assigned to a different role as instructed by the company.

2025年卒