layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Computational Scientist – AI/ML Engineer for Climate Science at University of Chicago | LAYIQ

Education: PhD in Computer Science, Applied Mathematics, Atmospheric Science, Physics, Earth System Science, or a related field with a strong AI/ML or computational science focus.
Experience: Minimum of two years of relevant research or professional experience in AI/ML, scientific computing, climate science, atmospheric science, or related computational research environments.
Technical Skills and Knowledge: Strong programming skills in Python and/or C++.
Experience with AI/ML frameworks such as PyTorch or TensorFlow.
Experience developing, training, and optimizing neural network and deep learning architectures.
Experience with Linux/UNIX environments and HPC systems.
Familiarity with job schedulers such as SLURM.
Experience deploying and optimizing workloads on GPU-accelerated systems.
Familiarity with climate, weather, atmospheric, or Earth system data workflows and computational challenges.
Understanding of distributed training, model scaling, and performance optimization for AI/ML applications.
Familiarity with scientific computing libraries such as NumPy, SciPy, pandas, xarray, and scikit-learn.
Experience working with large-scale scientific datasets and formats such as NetCDF and HDF5.
Experience applying AI/ML methods to climate, atmospheric, or earth system science problems.
Experience with climate and community modeling frameworks such as WRF or CESM.
Experience with container technologies and development tools such as Git and Docker.
Experience installing, optimizing, and profiling scientific software on HPC systems.
Familiarity with performance analysis and compiler optimization techniques.
Experience with distributed and parallel computing technologies such as MPI and OpenMP.
Experience with large-scale neural network architectures for processing spatiotemporal data, such as Vision Transformers (ViTs).
Experience with generative modeling with deep learning, such as flow matching or stochastic interpolants.
Preferred Competencies
Understand and translate researchers' scientific goals into computational requirements.
Work well with faculty and researchers.
Identify and gain expertise in appropriate new technologies and/or software tools.
Function as part of an interactive team while demonstrating self-initiative to achieve project's goals and Research Computing Center's mission.
Strong analytical skills and problem-solving ability.
Application Documents
CV or resume (required)
Cover letter (preferred)
The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.
When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.
Job Family
Research
Role Impact
Individual Contributor
Scheduled Weekly Hours
37.5
Drug Test Required
No
Health Screen Required
No
Motor Vehicle Record Inquiry Required
No
Pay Rate Type

Computational Scientist – AI/ML Engineer for Climate Science

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