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Overnight Computer Science Postdoc Jobs in Hammond, IN

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Overnight Computer Science Postdoc information

What is an overnight computer science postdoc?

An Overnight Computer Science Postdoc is a postdoctoral researcher in computer science who primarily works during nighttime hours. These positions typically involve conducting advanced research, collaborating on academic papers, and contributing to ongoing projects in areas like artificial intelligence, machine learning, or cybersecurity. Working overnight may be required to align with global research teams, utilize available computing resources, or accommodate personal schedules. Applicants generally need a recent Ph.D. in computer science or a closely related field. The role helps postdoctoral researchers gain further experience and prepare for faculty or industry positions.

What are the typical challenges faced by an overnight computer science postdoc and how can they be managed effectively?

An Overnight Computer Science Postdoc often faces the challenge of maintaining productivity and focus during non-traditional working hours, which can impact work-life balance and collaboration with daytime colleagues. Managing these challenges involves establishing a structured routine, utilizing collaboration tools to stay connected with team members, and setting clear communication expectations. Additionally, it's important to prioritize self-care and leverage flexible scheduling when possible to maintain overall well-being and research effectiveness.

What are the key skills and qualifications needed to thrive as an overnight computer science postdoc, and why are they important?

To thrive as an Overnight Computer Science Postdoc, you need a PhD in computer science or a related field, strong research skills, and expertise in your chosen area of study. Experience with programming languages (such as Python, Java, or C++), data analysis tools, and version control systems like Git is critical, along with familiarity with relevant computational frameworks. Excellent problem-solving abilities, self-motivation, and strong written and verbal communication skills help you excel in independent and collaborative research, especially during non-standard hours. These competencies enable you to contribute original findings, manage complex projects, and effectively communicate results within the academic community.

What is the difference between Overnight Computer Science Postdoc vs Research Scientist?

AspectOvernight Computer Science PostdocResearch Scientist
CredentialsPhD in Computer Science or related fieldMaster's or PhD, often with specialized expertise
Work EnvironmentAcademic or research institution, often with flexible hoursIndustry labs or corporate R&D, standard working hours
Employer & IndustryUniversities, research institutesTech companies, R&D divisions
Search & Comparison IntentUnderstanding academic vs industry roles, work hours, credentialsCareer transition, industry-specific roles

The Overnight Computer Science Postdoc typically involves academic research with flexible hours and a focus on advancing knowledge in computer science. In contrast, a Research Scientist usually works in industry, with standard hours and applied research goals. Both roles require advanced degrees, but their work environments and career paths differ significantly.

Computational Scientist - AI/ML Engineer for Climate Science

The University Of Chicago

Chicago, IL • On-site

$85 - $105/hr

Other

Medical, Retirement, PTO

Posted 2 days ago

New


University Of Chicago rating

8.1

Company rating: 8.1 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

163rd of 620 rated colleges and universities


Job description

## Computational Scientist – AI/ML Engineer for Climate ScienceApplyremote type: Hybridlocations: Hyde Park Campustime type: Full timeposted on: Posted Todayjob requisition id: JR34240**Department**Provost Research Computing Center**About the Department**The University of Chicago Research Computing Center (RCC), a unit within the Office of Research, provides advanced research computing resources and expertise to support computational and data-intensive research across the University. RCC enables research through centrally managed high-performance computing (HPC), storage, visualization, and AI infrastructure, along with scientific consulting, user support, education, and training. RCC also helps researchers leverage local, national, and cloud-based computational resources. The Office of Research oversees sponsored research administration, research development, and contract management across the University.**Job Summary**The job develops software to support the data acquisition, ingestion, and integration for research projects. Assists in the development of user interfaces and scalable back-end services to automate and accelerate the scientific output of multi-institutional research projects. The Research Computing Center (RCC) seeks an experienced Computational Scientist – AI/ML Engineer to support faculty, postdoctoral researchers, and graduate students conducting computational and AI-driven research. This position will contribute to a major new AI and climate computing initiative in collaboration with NVIDIA, the University of Chicago Data Science Institute (DSI), Argonne National Laboratory, University of Chicago Development Innovation Lab (DIL), AI for Climate (AICE), and Human-Centered Weather Forecasts (HCWF) supporting next-generation climate and Earth system AI research and infrastructure development. The successful candidate will collaborate closely with researchers to understand scientific challenges, develop and optimize AI/ML workflows, neural networks, and deploy scalable solutions on modern HPC and GPU-accelerated systems. This role includes supporting climate and geophysical science applications, enabling large-scale AI training and inference workflows, and contributing to the advancement of AI-enabled scientific discovery. The ideal candidate will have experience working at the intersection of AI/ML, climate science, and large-scale scientific computing environments. As part of RCC’s Computational Scientist team, the candidate will also contribute to user engagement, training, documentation, and grant support activities that advance computational research at the University of Chicago. This is a hybrid position requiring at least three days onsite per week.**Responsibilities*** Support computational applications, software, and workflows related to climate, atmospheric, geophysical, and earth system sciences.* Collaborate with researchers to translate scientific challenges into scalable AI/ML and computational solutions.* Deploy, optimize, and support AI/ML pipelines on HPC and GPU-accelerated systems.* Optimize large-scale training and inference workflows using distributed computing frameworks and performance analysis tools such as NVIDIA Nsight.* Assist researchers with compiling, debugging, profiling, tuning, and porting scientific applications.* Optimize system utilization, including CPU/GPU, memory, storage, and I/O performance.* Maintain and support scientific software environments, community codes, and research datasets relevant to climate and earth system science.* Consult with faculty and research groups to help them effectively utilize RCC, national computing facilities, and cloud resources.* Contribute technical expertise to grant proposals and collaborative research initiatives.* Stay informed on emerging AI methods, climate modeling advances, and GPU computing technologies relevant to Earth system science.* Develops and presents technical training materials and web-based documentation. Ensures timely systems support and updates. Assists in conducting information security assessments and risk analysis of computing environment.* Evaluates past and present technologies to help develop new tools. Ensures all the new tools have been through quality control reviews.* Performs other related work as needed.**Minimum Qualifications****Education:**Minimum requirements include a college or university degree in related field.**Work Experience:**Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.**Certifications:****---****Preferred Qualifications****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**Salary **FLSA Status**Exempt **Pay Range**$85,000.00 - $105,000.00The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.**Benefits Eligible**YesThe University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.**Posting Statement**The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination. #J-18808-Ljbffr

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