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操作画面は日本語です。企業が掲載した求人の職種名や説明文は原文のまま表示され、英語の場合があります。

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Physical Sciences Expert - Terminal Bench

Weekday AI

リモート勤務

勤務地
Remote (India)
掲載日
2026年10月19日

応募する前に、企業のウェブサイトで現在も募集中かどうかと詳しい条件を確認してください。

仕事内容

操作画面は日本語です。企業が掲載した求人の職種名や説明文は原文のまま表示され、英語の場合があります。

This role is for one of our clients Role Details Employment Type: Contract Location: Bangladesh, India, Pakistan, Indonesia, Egypt, Ghana, Nigeria, Turkey, Brazil, and Colombia Contract Duration: 5 weeks Start Date: Immediate Work Commitment: 40 hours per week, with at least 4 hours of daily overlap with Pacific Standard Time (PST) Compensation: $300 per approved task Average Task Completion Time: 6–8 hours Contract Benefits: No medical benefits or paid leave About the Role We are seeking highly qualified Physical Sciences Experts to develop realistic, terminal-based scientific computing tasks for AI benchmarking and evaluation. The role involves translating authentic workflows from physics, chemistry, materials science, astronomy, and computational science into reproducible, technically rigorous benchmark environments. You will develop scientific inputs, computational models, executable reference solutions, automated tests, and objective grading criteria. Your work will help assess whether AI agents can reason through complex scientific problems, use command-line tools effectively, debug calculations, execute simulations, and generate accurate, reproducible scientific outputs. The ideal candidate combines advanced academic or research expertise in a relevant physical-science discipline with strong programming skills and practical experience in computational modeling, numerical analysis, and scientific data processing. Core Scientific Domains Candidates should have expertise in at least one of the following areas: Physics and computational physics Chemistry and computational chemistry Materials science and materials modeling Astronomy and cosmology Thermodynamics Quantum mechanics Statistical mechanics Numerical and computational science Key Responsibilities Scientific Task Design: Develop challenging, multi-step terminal-based tasks based on authentic physical-science research and computational workflows. Environment Development: Build self-contained, reproducible computational environments with appropriate scientific software, dependencies, and configurations. Scientific Input Preparation: Create datasets, molecular structures, simulation parameters, experimental data, and model configurations. Reference Solution Development: Implement reliable scientific solutions using Python, Bash, C/C++, Julia, or other relevant programming languages and domain-specific tools. Automated Testing: Develop tests to validate numerical accuracy, physical consistency, convergence, expected output structures, and task completion. Computational Modeling: Design tasks involving simulations, numerical modeling, data fitting, optimization, spectroscopy, molecular analysis, and scientific visualization. Scientific Validation: Define appropriate units, numerical tolerances, boundary conditions, physical constraints, and expected scientific behavior. Reproducibility: Ensure tasks execute reliably in controlled environments without requiring runtime downloads or undocumented dependencies. Debugging and Optimization: Troubleshoot dependency conflicts, numerical precision issues, solver instability, computational performance, and file-format problems. Documentation: Clearly communicate scientific assumptions, computational methods, expected outputs, edge cases, and limitations to reviewers. Required Qualifications A PhD in Engineering or a relevant physical-science discipline, or postdoctoral experience or equivalent advanced technical experience in a relevant field. Strong expertise in at least one core domain, such as physics, chemistry, materials science, astronomy, cosmology, or computational science. Proficiency in Python, C/C++, Julia, Bash, or another programming language used for scientific computing. Experience with numerical methods, scientific simulations, computational modeling, or quantitative data analysis. Familiarity with Linux and terminal-based development environments. Ability to independently develop, debug, and validate scientific computational workflows. Strong understanding of physical units, numerical precision, scientific constraints, and reproducibility. Excellent analytical, problem-solving, and technical communication skills. Preferred Qualifications Experience with scientific computing libraries such as NumPy, SciPy, pandas, Matplotlib, SymPy, or JAX. Familiarity with molecular dynamics, quantum chemistry, finite-difference methods, Monte Carlo simulations, optimization, or statistical modeling. Experience with domain-specific tools such as OpenMM, ASE, RDKit, Psi4, LAMMPS, or GROMACS. Familiarity with Docker, Conda, Git, continuous integration systems, and automated testing frameworks. Experience with high-performance computing (HPC) systems or computationally intensive scientific workloads. Additional Advantages Experience evaluating AI coding agents or terminal-based AI systems. Background in research software engineering or scientific benchmark development. Experience creating automated graders and objective evaluation frameworks. Publications or open-source contributions in computational science or related research areas. Experience converting experimental or research workflows into reproducible computational packages. Contract and Compensation Details This is a 5-week, full-time contractor assignment requiring 40 hours of work per week and at least 4 hours of daily overlap with PST. Compensation follows a pay-per-task model, with $300 paid for each approved task that meets the project's specifications and acceptance criteria. Each task is expected to take approximately 6–8 hours on average, depending on complexity. The contract does not include medical benefits or paid leave. Candidates must be available to start immediately and commit to the required schedule throughout the engagement. Selection Process Interest Check Form: Complete the initial application and confirm interest in the assignment. Mandatory Screening Assessment: Complete the Terminal Bench screening test, lasting approximately 20 minutes. Specialized Physical Sciences Assessment: Complete one 40-minute assessment in the relevant subject area: Astronomy and Cosmology Physics Materials Science Chemistry Delivery Manager Review: The application and assessment results will be reviewed before the final selection decision. Total assessment time: Approximately 60 minutes, comprising the mandatory 20-minute screening test and one 40-minute subject-specific test. Candidates should take only one specialized assessment after completing the screening test. Important Application Instructions Candidates must use the same email address for the Interest Check Form and the agency portal submission. Applicants should be ready to begin immediately and meet the full-time availability requirements.

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必須条件と歓迎条件を分けて確認し、勤務時間、報酬、勤務地が掲載されている場合は目を通しましょう。リモート勤務でも、居住国、就労資格、勤務時間帯が指定されることがあります。現在の募集状況と詳しい条件は企業に確認してください。

募集要件に関連する実際の経験を選び、自分の役割と貢献を説明しましょう。数値は根拠がある場合にのみ使ってください。企業の応募方法に従い、送信前に連絡先、内容、PDFの表示を確認しましょう。

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仕事探しに関するよくある質問

英語の求人が表示されるのはなぜですか?

職種名や説明文は企業が作成したものです。条件や要件を変えないように原文を掲載しています。操作画面とこのガイドは日本語です。日本語の検索で見つからない場合は、「software engineer」のように、掲載言語の職種名やスキル名でも検索してみてください。検索語が自動翻訳されるわけではありません。

リモート求人なら、どの国からでも働けますか?

必ずしもそうではありません。居住国、就労資格、勤務時間帯が指定されている場合があります。元の求人ページで条件を確認してください。記載がない場合は、自分の居住地から応募できると判断する前に企業へ確認しましょう。リモートという表示だけでは、勤務地の制限がないことは分かりません。

検索結果が出ない場合はどうすればよいですか?

より一般的な職種名や一つのスキルで検索し、条件を一つずつ外してみてください。同じような仕事でも企業によって呼び方が異なります。特定の求人が見つからなくなった場合は、企業の採用ページで求人番号を探しましょう。検索条件を広げても、終了した募集が再開するわけではありません。

ResumizeAIから応募が送信されますか?

応募ボタンは外部サイトを開きます。企業または採用サービスの案内に従い、そのサイトで送信を完了してください。ResumizeAIで応募書類を作成しただけでは応募は送信されません。リンク先が企業のトップページの場合は、該当する募集を探してから手続きを進めましょう。

応募書類とカバーレターはどう調整すればよいですか?

募集要件と、自分が説明できるプロジェクト、業務、成果を結び付けます。経験していない技術や実績を加えず、関連する経験を分かりやすく示してください。カバーレターでは応募理由を具体例とともに伝えます。指定された言語とファイル形式に従い、送信前に両方の書類を確認しましょう。