🌎 Scientific Computing / Research Engineering Expert — Earth Sciences | Remote Job at Turing

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🌎 Scientific Computing / Research Engineering Expert — Earth Sciences | Remote Job at Turing Are you an Earth Sciences expert with strong scientific computing and programming skills? Turing is seeking experienced researchers and technical professionals to develop realistic, terminal-based scientific tasks for Terminal Bench Science. In this role, you will transform real-world Earth Sciences workflows into computational benchmark tasks that test how effectively AI agents process scientific data, run models, troubleshoot pipelines, and produce scientifically accurate results. The project covers areas such as climate science, atmospheric processes, geophysics, oceanography, geology, hydrology, remote sensing, and environmental modeling. 💰 Payment: $300 per approved task Please review the project requirements, weekly commitment, and task-based payment structure before applying. 📌 Job Overview - 🏢 Company: Turing - 💼 Job Title: Scientific Computing / Research Engineering Expert — Earth Sciences - 🌍 Work Mode: Remote - 🧪 Project: Terminal Bench Science - 📄 Employment Type: Contractor Assignment - ⏳ Contract Duration: 5 weeks - 🚀 Expected Start: Next week, according to the supplied listing - 🕒 Working Commitment: At least 6 hours per day - 📅 Weekly Hours: Minimum 40 hours - 🌐 Time-Zone Requirement: 4 hours of overlap with Pacific Standard Time (PST) - 💵 Payment Type: Pay per task - 💰 Payment Rate: $300 per approved task - 🎁 Referral Bonus: $150 shown on the listing; this is a referral incentive, not the applicant's compensation. Important: Payment is based on approved tasks, not a guaranteed hourly salary. The number of tasks approved and the total earnings are not specified in the provided description. 🏢 About the Project Terminal Bench Science focuses on developing realistic scientific tasks that AI agents can attempt in terminal-based computing environments. For this Earth Sciences project, experts will create tasks based on authentic scientific workflows. These tasks may require an AI agent to process environmental datasets, perform geospatial analysis, run numerical simulations, debug scientific software, and generate outputs that can be checked objectively. The goal is to build reliable benchmarks for evaluating AI systems on complex scientific computing problems. 🔍 Key Responsibilities Selected experts may be responsible for the following activities: - 🌎 Convert real-world Earth Sciences workflows into self-contained terminal-based benchmark tasks. - 🛰️ Prepare climate, weather, geospatial, geological, hydrological, and oceanographic datasets. - 💻 Build reproducible computational environments using scientific libraries and command-line tools. - 🐍 Develop expert solutions using Python, R, Julia, Bash, or other scientific programming languages. - 📊 Create tasks involving time-series analysis, remote sensing, numerical modeling, forecasting, interpolation, and environmental risk analysis. - 🧪 Design objective grading criteria to evaluate scientific outputs and AI agent performance. - 📐 Validate coordinate systems, units, timestamps, missing data, and scientific assumptions. - ✅ Build automated tests for numerical accuracy, file formats, metadata, and reproducibility. - 🔧 Troubleshoot geospatial projections, dependencies, large datasets, performance, and numerical stability. - 📝 Document data sources, expected results, edge cases, limitations, and evaluation methods. 🎓 Required Qualifications Applicants should meet the following requirements: - Ph.D., postdoctoral experience, or equivalent advanced technical experience in Earth Sciences or a closely related field. - Strong expertise in at least one relevant discipline, such as: - Climate Science - Atmospheric Science - Geophysics - Oceanography - Geology - Hydrology - Remote Sensing - Environmental Modeling - Earth-System Science - Strong programming skills in Python, R, Julia, Bash, or another scientific programming language. - Hands-on experience with scientific data processing, numerical modeling, geospatial analysis, environmental datasets, or time-series analysis. - Comfortable working independently in Linux and terminal-based environments. - Ability to build, debug, and validate reproducible computational workflows. - Strong understanding of scientific quality control, uncertainty, spatial and temporal data, and numerical accuracy. 🛠️ Preferred Technical Skills Experience with the following tools and technologies may be beneficial: Scientific and geospatial libraries - NumPy - pandas - SciPy - xarray - rasterio - GeoPandas - Cartopy - GDAL Scientific data formats - NetCDF - HDF5 - GeoTIFF - Shapefiles - GRIB Development and infrastructure tools - Docker - Conda - Git - CI/CD - Automated testing - High-Performance Computing (HPC) environments Experience with climate, weather, satellite, seismic, oceanographic, geological, or hydrological datasets is also relevant. ⭐ Additional Advantages Candidates may have an advantage if they possess: - Research software engineering experience. - Scientific benchmarking or automated grader development experience. - Experience evaluating AI coding agents or terminal-based AI systems. - Experience developing AI evaluation tasks and benchmark datasets. - Relevant academic publications or open-source contributions in Earth Sciences, environmental science, geospatial analysis, or computational science. These additional qualifications are described as desirable rather than universally mandatory. 💰 Payment Details This opportunity uses a pay-per-task payment model. Detail Information Payment per approved task $300 Payment method Task-based Contract duration 5 weeks Weekly commitment Minimum 40 hours Daily commitment At least 6 hours PST overlap 4 hours Employment type Contractor The stated payment is $300 for each approved task. The listing does not specify how many tasks an individual may complete, how long approval takes, or the maximum possible earnings. Applicants should confirm task acceptance criteria, payment timing, and other contract terms with Turing before starting work. 🌐 Working Hours and Contract Conditions Selected candidates must be prepared to: - Commit at least 6 hours per day. - Work a minimum of 40 hours per week. - Maintain 4 hours of overlap with PST. - Complete the project within the expected 5-week contract period. This is a contractor assignment. The listing states that medical and paid leave are not provided. Apply Now