About this role
Computational Life Sciences Lead
This role is part of the “Weekday Partner Network”, i.e., posted by one of our clients
About the role
Role Overview: We are seeking an experienced expert in civil or structural engineering with strong computational and programming skills to lead a team of 5–10 technical trainers. The team develops challenging engineering tasks for advanced AI training and evaluation. The role involves reviewing engineering models, simulations, computational workflows, and automated graders for technical accuracy and reproducibility, mentoring trainers, and maintaining high-quality standards.
Requirements
- Ph.D., postdoctoral experience, or equivalent advanced technical expertise in Civil Engineering, Structural Engineering, Geotechnical Engineering, or a closely related discipline.
- Strong programming skills in Python, C/C++, Julia, Fortran, or MATLAB/Octave, with proficiency in Linux and terminal-based environments.
- Hands-on expertise in at least one area such as structural analysis, finite-element analysis (FEA), earthquake engineering, geotechnical modeling, or hydraulic/hydrological modeling.
- Strong understanding of engineering principles, numerical methods, computational simulations, and model validation.
- Working knowledge of engineering design standards such as ASCE 7, ACI, AISC, Eurocodes, or IS codes.
- Experience reviewing engineering simulations, computational models, research outputs, or complex technical work.
- Experience mentoring, reviewing, or leading small technical or research teams.
- Excellent written communication skills and the ability to provide precise, constructive technical feedback.
Preferred Qualifications:
- Familiarity with engineering tools such as OpenSees/OpenSeesPy, Code_Aster, CalculiX, FEniCS, Gmsh, EPANET, SWMM, HEC-RAS, or MODFLOW.
- Experience with commercial engineering software such as SAP2000, ETABS, Abaqus, PLAXIS, or STAAD.Pro.
- Experience with nonlinear time-history analysis, performance-based design, reliability analysis, or structural health monitoring.
- Familiarity with Docker, Git, CI/CD pipelines, and automated testing.
- Experience developing or evaluating AI coding agents, terminal-based agents, or AI-generated engineering solutions.
- Professional engineering licensure such as PE, SE, CEng, or equivalent.
- Industry experience in buildings, bridges, transportation networks, water systems, or major infrastructure projects.
- Prior experience in AI training, technical quality control, benchmark development, or evaluation programs.
Project Details:
- Commitment: Full-time — minimum 40 hours/week, with at least 4 hours of overlap with PST.
- Duration: 4 weeks.
- Start Date: Expected to begin next week.
- Employment Type: Contractor assignment (no medical or paid leave).
- Role
Responsibilities
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Lead a pod of approximately 5–10 trainers, review engineering tasks and simulation outputs, validate reference solutions and automated graders, ensure technical accuracy and reproducibility, and maintain quality standards throughout task development.
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Good-to-have skills
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Civil EngineeringStructural EngineeringGeotechnical EngineeringPythonC/C++JuliaFortranMATLABOctaveLinuxTerminalStructural AnalysisFinite-Element AnalysisFEAEarthquake EngineeringGeotechnical ModelingHydraulic ModelingHydrological ModelingNumerical MethodsComputational SimulationsModel ValidationASCE 7ACIAISCEurocodesIS CodesOpenSeesOpenSeesPyCode_AsterCalculiXFEniCSGmshEPANETSWMMHEC-RASMODFLOWSAP2000ETABSAbaqusPLAXISSTAAD.ProNonlinear Time-History AnalysisPerformance-Based DesignReliability AnalysisStructural Health MonitoringDockerGitCI/CDAutomated TestingAI Coding AgentsProfessional Engineering LicensurePESECEng