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Geometric Deep Learning Jobs in Tennessee (NOW HIRING)

Math 1 Tutor

Kingsport, TN · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Math 1 Tutor

Chattanooga, TN · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Math 1 Tutor

Memphis, TN · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Math 1 Tutor

Nashville, TN · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Math 1 Tutor

Murfreesboro, TN · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Math 1 Tutor

Knoxville, TN · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Geometry Tutor

Memphis, TN · Remote

$18 - $40/hr

Deep knowledge of geometric proofs, triangle congruence and similarity, circles, polygons ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Geometry Tutor

Knoxville, TN · Remote

$18 - $40/hr

Deep knowledge of geometric proofs, triangle congruence and similarity, circles, polygons ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Geometry Tutor

Murfreesboro, TN · Remote

$18 - $40/hr

Deep knowledge of geometric proofs, triangle congruence and similarity, circles, polygons ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Geometry Tutor

Nashville, TN · Remote

$18 - $40/hr

Deep knowledge of geometric proofs, triangle congruence and similarity, circles, polygons ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Geometry Tutor

Kingsport, TN · Remote

$18 - $40/hr

Deep knowledge of geometric proofs, triangle congruence and similarity, circles, polygons ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Geometry Tutor

Chattanooga, TN · Remote

$18 - $40/hr

Deep knowledge of geometric proofs, triangle congruence and similarity, circles, polygons ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

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Geometric Deep Learning information

What is geometric deep learning?

Geometric deep learning is a branch of machine learning focused on designing neural networks that operate on non-Euclidean data such as graphs and manifolds. It involves techniques like graph neural networks and requires understanding of both deep learning and geometric structures, often using tools like PyTorch or TensorFlow. Professionals in this field develop models for applications like social network analysis, 3D shape recognition, and molecular modeling.

What is the difference between Geometric Deep Learning vs Data Scientist?

AspectGeometric Deep LearningData Scientist
Required CredentialsAdvanced degrees in computer science, machine learning, or related fieldsBachelor's or master's in data science, statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness analytics, product teams, consulting firms
Industry UsageAI, robotics, computer vision, graph analysisBusiness intelligence, marketing, finance, healthcare

Geometric Deep Learning focuses on applying deep learning techniques to non-Euclidean data like graphs and manifolds, often requiring advanced technical skills. Data Scientists analyze and interpret data to inform business decisions, typically working with structured data and statistical tools. While both roles involve data analysis, Geometric Deep Learning is more research-oriented and specialized in AI development, whereas Data Scientists focus on practical data insights across industries.

What are some common challenges faced when working on Geometric Deep Learning projects, and how can they be addressed?

One common challenge in Geometric Deep Learning is dealing with the complexity and diversity of data structures, such as graphs, point clouds, or manifolds. These data types often require specialized neural network architectures and custom preprocessing steps, which can be more complex than traditional deep learning tasks. Collaboration with domain experts and staying updated with the latest research are crucial for overcoming these obstacles. Additionally, debugging and visualizing the learning process can be more challenging, so employing robust evaluation metrics and visualization tools is highly recommended.

What are the key skills and qualifications needed to thrive as a Geometric Deep Learning Engineer, and why are they important?

To excel as a Geometric Deep Learning Engineer, you need a strong background in mathematics, machine learning, and computer science, typically supported by an advanced degree in a related field. Proficiency with deep learning frameworks like PyTorch or TensorFlow, as well as experience with graph neural networks (GNNs) and geometric data structures, is essential. Strong analytical thinking, problem-solving abilities, and collaborative communication are key soft skills for innovating and working with interdisciplinary teams. These skills are crucial for developing cutting-edge models that leverage geometric data, enabling impactful solutions across domains such as computer vision, biology, and social network analysis.

Which 5 jobs will survive AI?

Geometric Deep Learning specialists are likely to continue in demand due to their expertise in advanced neural network architectures and 3D data processing. Jobs involving complex problem-solving, creativity, and domain-specific knowledge—such as data scientists, AI researchers, software engineers, cybersecurity analysts, and healthcare professionals—are expected to persist as AI tools augment rather than replace these roles. Continuous learning and proficiency with AI frameworks like TensorFlow or PyTorch enhance job security in these fields.

What engineer makes $500,000 a year?

Senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries like technology or finance. These roles often require expertise in programming, system design, and sometimes leadership or management responsibilities.
What are popular job titles related to Geometric Deep Learning jobs in Tennessee? For Geometric Deep Learning jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Geometric Deep Learning jobs in Tennessee look for? The top searched job categories for Geometric Deep Learning jobs in Tennessee are:
What cities in Tennessee are hiring for Geometric Deep Learning jobs? Cities in Tennessee with the most Geometric Deep Learning job openings:
Postdoctoral Research Associate - AI Models for Power Grid System

Postdoctoral Research Associate - AI Models for Power Grid System

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Oak Ridge National Laboratory rating

9.3

Company rating: 9.3 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

3rd of 103 rated laboratories


Job description

Requisition Id 16687
Overview:
As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.
The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected to bring strong expertise in scalable deep learning, high-performance computing (HPC), scalable data management, Linux environments, and production-quality scripting for HPC workflows.
Major Duties/Responsibilities:
  • Participate in the design, implementation, and deployment of scalable AI/DL models for power grid systems, including surrogate models and foundation-model workflows for OPF and related grid simulation tasks.
  • Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and institutional clusters.
  • Write robust Linux bash scripts and job submission scripts for SLURM and PBS environments, including multi-node GPU/CPU workflows, monitoring, restart, and post-processing pipelines.
  • Author peer reviewed papers for journals and conferences, technical reports, open-source software, and represent the organization by making technical presentations at workshops and conferences.
  • Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, electrical engineers, domain scientists, and applied mathematicians conducting basic and applied AI/DL research in support of the Laboratory's missions.

Basic Qualifications:
  • A PhD in computer science or an AI-related field completed within the last 5 years.
  • Demonstrated expertise in scalable deep learning, including distributed training and/or large-scale inference using modern AI frameworks such as PyTorch.
  • Demonstrated experience with high-performance computing systems, including multi-node workflows on CPU and/or GPU clusters.
  • Demonstrated expertise in scalable data management for AI/ML workflows, including efficient data preprocessing, storage, streaming, and I/O for large scientific datasets.
  • Demonstrated experience writing SLURM and PBS job submission scripts for HPC clusters, including batch workflows, job arrays, environment setup, and restart logic.
  • Demonstrated expertise with the Linux operating system, bash scripting, Git, Python, and reproducible software environments.
  • Demonstrated expertise in writing advanced software in Python and in the design and implementation of deep learning algorithms.
  • Expertise in object-oriented programming, scripting languages, and modern software engineering practices for research codes.
  • Demonstrated effective written and oral communication skills, a proven publication record, and effective interpersonal skills.

Preferred Qualifications:
  • Knowledge of graph neural networks and other geometric deep learning approaches for graph-structured scientific or engineering data.
  • Background in electrical engineering, power systems, grid modeling, or power system optimization.
  • Experience with optimal power flow and grid simulation solvers or toolchains, such as MATPOWER, PSS/E, PowerModels, or related open-source or commercial packages.
  • Experience working in a multi-disciplinary research environment that follows modern software quality standards, including version control, unit testing, documentation, and continuous integration.
  • Motivated self-starter with the ability to work independently, participate creatively in collaborative teams, function well in a fast-paced research environment, and adapt to evolving project needs.

Special Requirements:
Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.
Candidates are asked to submit a detailed cover letter describing their experience relative to the duties and qualifications described in this posting with their application.
Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.
Instructions to upload documents to your candidate profile:
  • Login to your account via jobs.ornl.gov
  • View Profile
  • Under the My Documents section, select Add a Document

Technical questions:
Massimiliano Lupo Pasini (lupopasinim@ornl.gov), Alex Plotkowski (plotkowskiaj@ornl.gov)
About ORNL:
As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.
ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.
Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.
This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.
If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.
ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.

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