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2024 New Graduates-Material Discovery Engineer ・Researcher 新卒エンジニア・リサーチャー(材料探索)

LocationOtemachi Tokyo Japan
RemoteSee job post for details
First listedIn the last 10 months

Job Description

We are recruiting researchers and engineers for material exploration.

Numerical techniques in chemistry and materials science have made remarkable progress, and in recent years, computational development of new materials has been attracting attention.

PFN has developed Matlantis™, a general-purpose atomic-level simulator, in collaboration with ENEOS Corporation, in order to develop innovative materials by highly integrating computational science and materials development.

PFN is working on further technological development of Matlantis and physical simulation technology based on deep learning, with the goal of realizing material exploration and property prediction that far exceeds the conventional limits of application. We are looking for people who want to develop unprecedented simulation technology and material proposal methods by combining computational science and deep learning, and who want to develop new materials together with our customers by doing so.

We welcome applications from those who have knowledge and experience in related fields, as well as those who share this ambitious goal and are enthusiastic about it.

<Materials Discovery Team Mission>

  • Realization of a sustainable society through innovative materials development

  • Develop innovative technologies based on materials science, physical chemistry, and computational chemistry for materials development

<Specific duties are expected to include the following (Flexible depending on skills and scope of interest)>

  • Further technical development of Matlantis.
  • Utilize knowledge of deep learning and physical chemistry to improve the architecture used in Matlantis to further increase performance.
  • Investigate and improve areas where Matlantis currently has difficulty achieving prediction accuracy.
  • Propose and implement additional functionality development for Matlantis based on the latest research trend and customer requests.
  • Joint development of materials with other companies
  • Solve customer problems by utilizing the computational resources of Matlantis and PFN.
    - Listening to customer issues and proposing solutions from a physical and computational chemistry perspective.
    - Develop technologies for innovative materials development and solve customer issues based on them.
    - Conduct regular customer reporting and receive customer feedback to develop new technologies.
    - Deliver developed solutions to customers.
  • Solve challenges using materials informatics and deep learning.
    - Solve customer issues in manufacturing and research using materials informatics.
    - Identify and solve customer issues in materials development using deep learning insights.
  • Innovative research and real-world applications
  • Keep abreast of the latest research and papers, and propose and implement innovative technological developments with enthusiasm.
  • Through joint research with universities and companies, develop new technologies that do not exist in the world and apply them to real-world material development.
  • Collaborate with other teams and conduct technical exchanges within the company. Keep abreast of the latest technologies in various fields.

<Related links for this position>




<Materials Discoveryチームのミッション>

  • 革新的なマテリアル開発による持続可能な社会の実現。
  • 素材開発のための、材料科学・物理化学・計算化学に基づく革新的な技術の開発。


  • Matlantisの更なる技術開発

  • 深層学習と物理化学の知識を活かし、Matlantisに用いられているアーキテクチャを改良し、更なる性能向上を目指す。

  • 現在のMatlantisの課題を切り出し、原因究明と改善を実施する。

  • 最新の研究動向や顧客要望から、Matlantisの追加機能開発の提案・実施をする。

  • 他社との材料の共同開発

  • 顧客課題をMatlantisおよびPFNの計算資源を活用して解決する。
    - 顧客課題を聞き取り、物理化学・計算化学的な視点から解決方法を考えて提案する。
    - 革新的な材料開発のための技術開発をし、それらを活用して顧客課題の解決をする。
    - 定期的な顧客への報告を実施し、顧客からのフィードバックをもとに新規技術を開拓する。
    - 開発したソリューションを顧客に納品する。

  • マテリアルズインフォマティクスおよび深層学習を用いた課題解決。
    - 製造・研究での顧客課題をマテリアルズインフォマティクスを用いて解決する。
    - 深層学習の知見を活かし、材料開発における顧客課題を特定・解決する。

  • 革新的な研究と現実への適用

  • 最新の研究・論文を把握し、熱意をもって革新的な技術開発を提案・実行する。

  • 大学・企業との共同研究を通して、世の中にない新たな技術を開発し、それを現実の素材開発に活かす。

  • 他チームとの連携・社内での技術交流を実施。様々な分野の最新技術を把握する。


Matlantis HP:https://matlantis.com/ja/

Matlantis 計算事例:https://matlantis.com/ja/cases#calculation

Matlantis 論文: https://www.nature.com/articles/s41467-022-30687-9

Matlantis 論文解説ブログ:https://tech.preferred.jp/ja/blog/development-of-universal-neural-network-for-materials-discovery/

Materials Science Blog: https://tech.preferred.jp/blog/area/chemoinformatics-and-materials-science/





  • Knowledge and motivation

  • Basic knowledge or interest in either physics, chemistry, or materials science

  • Basic knowledge of machine learning and deep learning

  • Ability to follow and implement the latest paper trends

  • In-depth knowledge and experience in your field of expertise.

  • Willingness to constantly learn new domain knowledge

  • Ability to actively engage in discussions with engineers from different fields and companies.

  • Interest in solving problems using computer-science knowledge
    - Always keeping up with the cutting-edge technology with the goal of becoming familiar with all disciplines of computer science

  • Experience

  • Experience in setting and solving problems
    - A series of experiences from problem investigation and problem formulation, trial and error, to the compilation of results
    - For example, dissertations, conference presentations, research internships, and various other extracurricular activities

  • Programming experience capable of carrying out research activities
    - Ability to understand computer architecture and create programs with awareness of software execution efficiency and computational complexity. Specifically :
    - Ability to use tools to find out where the major computation time is accounted for in the programs you have written
    - Ability to estimate the computation complexity in the program you were involved in by referring to the materials
    - Ability to write a simple numerical simulation, such as a ball bouncing around in a box, on one's own, using the appropriate time and materials

  • 知識・意欲
    - 物理・化学・材料科学いずれかに対する基本的な知識や関心
    - 機械学習・深層学習についての基礎的な知識
    - 最新の論文の動向を追いかけ、実装ができる能力
    - 自分の専門分野に関する深い知見と経験があること
    - 常に新しいドメインの知識を学ぶ意欲
    - 違う分野、企業のエンジニアと積極的に議論ができること
    - コンピュータサイエンスの知識を活用した課題解決への興味
    - コンピューターサイエンスのすべての分野への精通を目指し、常に最先端の技術を追いかけ続けること

  • 経験
    - 課題を設定し、解決した経験
    - 問題の調査と課題の切り出し、試行錯誤、結果のまとめに至る一連の経験
    - 例えば、学位論文、学会発表、研究インターンシップ、その他種々の課外活動など
    - 研究活動を遂行可能なプログラミング経験
    - コンピューターアーキテクチャを理解し、ソフトウェアの実行効率や、計算量を意識したプログラムの作成ができる。具体的には:
    - ツールを利用して、自分の書いたプログラムで主要な計算時間を占めている箇所を調べることができる
    - 資料にあたることで、自分の携わったプログラムの計算量を見積もることができる
    - 適切な時間と資料を使うことで、箱の中をボールが跳ね回るなどの素朴な数値シミュレーションを独力で書くことができる


※You do not need to have all of the skills listed below. We expect you to have excellent expertise in any of them.


  • Experience in computational chemistry and computational materials science. For example, in-depth knowledge of and experience implementing and using techniques such as quantum chemical calculations, molecular dynamics methods, device simulation, etc.

  • Experience in research and development and writing papers on the integration of physical simulation and machine learning.

  • Knowledge of and experience developing computational chemistry software and ancillary tools, or experience implementing similar software. For example, GAUSSIAN, VASP, GROMACS, LAMMPS, ASE, etc.

  • Experience in research and development and writing papers in the field of cheminformatics and materials informatics

  • Machine learning and deep learning related research and development experience

  • Interest in and implementation experience with computational efficiency and optimization related to physical simulation

  • Achievements/experience in programming competitions, game AI contests, data analysis contests (Kaggle, etc.), etc. Knowledge, implementation, and experience using mathematical optimization, search, and numerical analysis.

  • Experience in application development or operation (any environment or genre of software), development of libraries, Unix/Linux server operations

  • 計算化学・計算材料科学の経験。例えば、量子化学計算、分子動力学法、デバイスシミュレーション等の技法に対する深い知識や実装経験、使用経験。

  • 物理シミュレーションと機械学習の融合に関する研究開発・論文執筆経験

  • 計算化学ソフトウェアや補助ツールに対する知識、開発経験、あるいは類似のソフトウェアの実装経験。例えば、GAUSSIAN, VASP, GROMACS, LAMMPS, ASEなど

  • ケモインフォマティクス・マテリアルズインフォマティクス分野での研究開発・論文執筆経験

  • 機械学習・深層学習関連の研究・開発経験

  • 物理シミュレーションに関する計算効率化、最適化についての興味や実装経験

  • プログラミング競技コンテスト、ゲームAIコンテスト、データ分析コンテスト(Kaggleなど)などの実績・経験。数理最適化、探索、数値解析などの知識・実装・使用経験。

  • アプリケーション開発もしくは運用経験(環境やジャンルを問わず)、ライブラリの開発経験、Unix/Linuxサーバ運用経験

<Required documents in addition to a resume>

  • List of publications (if any)

  • 出版物のリスト (ある場合)


  • In materials exploration, we aim to discover new materials that will have a revolutionary impact on the world.
  • We are able to utilize our ample computational resources for research and development.
  • An environment where you can easily ask questions and consult with in-house engineers who are researching the cutting edge of their respective fields.
  • An environment where people are encouraged to boldly tackle difficult and challenging issues.
  • 材料探索では、世界に革新的インパクトを与えるような新物質の発見を目指している。
  • 潤沢な計算資源を利用した研究開発ができる。
  • 各分野の最先端を研究している社内の技術者に気軽に質問・相談が出来る環境。
  • 難しい課題・挑戦的な課題にも果敢に取り組むことが推奨されている環境。


雇用形態 Type of Employment

  • 正社員試用期間3ヶ月(本採用と同条件)
  • Full-time regular employment
  • Probation period: 3 months (under the same condition as regular employment)

勤務場所 Location

  • 東京都千代田区大手町1-6-1大手町ビル
  • Otemachi Bldg., 1-6-1 Otemachi, Chiyoda-ku, Tokyo

勤務体系 Work System

  • 土曜日、日曜日、国民の祝日、国民の休日、 その他(慶弔、年末年始)
  • 専門労働型裁量労働制(みなし労働時間:8時間)もしくはフレックス制
  • 当社規定による年次有給休暇制度
  • Five-day workweek (Saturdays and Sundays off), public holidays, New Year’s holiday
  • Discretionary-work (deemed work hours: 8 hours) or Flex-time system
  • Annual paid leave based on company regulations

待遇 Compensation

  • 経験、業績、能力、貢献に応じて、当社規定により優遇
  • 年2回見直し
  • 基本給に加え、会社業績および個人のパフォーマンスに応じたボーナス(年2回、4月/10月)
  • 交通費支給
  • Experience, performance, skills, contribution are taken into consideration.
  • Periodic assessment (2 times a year)
  • In addition to basic salary, bonuses are paid based on company’s performance and individual contribution. (Twice a year: Apr/Oct)
  • Commutation expenses

福利厚生 Welfare

  • 社会保険完備(厚生年金保険、健康保険、雇用保険、労災保険)
  • 有給休暇、産前産後休暇、育児休暇、慶弔休暇等
  • 定期健康診断実施
  • ラップトップPC購入補助
  • 確定拠出年金制度
  • Various social insurance programs: pension insurance, health insurance, employment insurance, workers’ compensation
  • Vacation: maternity leave, parental leave, congratulation or condolence leave
  • Regular health checks
  • Allowance for purchasing a laptop PC.
  • Defined contribution pension

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