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Geometric Deep Learning Jobs in Massachusetts (NOW HIRING)

Xometry

Staff Data Scientist

Waltham, MA · Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Deep expertise in Geometric Deep Learning, Computer Vision (3D mesh/B-Rep processing), or Generative AI is highly preferred given the focus on native 3D geometry * Strategic Delivery: Proven ability ...

Xometry

Staff Data Scientist

Waltham, MA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Deep expertise in Geometric Deep Learning, Computer Vision (3D mesh/B-Rep processing), or Generative AI is highly preferred given the focus on native 3D geometry * Strategic Delivery: Proven ability ...

Cisco

Applied AI Scientist

Waltham, MA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE ... Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems ...

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All JobsGeometric Deep Learning JobsGeometric Deep Learning Jobs in Massachusetts

Geometric Deep Learning information

What are the key skills and qualifications needed to thrive as a geometric deep learning engineer?

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.

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 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 popular job titles related to Geometric Deep Learning jobs in Massachusetts?

For Geometric Deep Learning jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Geometric Deep Learning jobs in Massachusetts look for?

The top searched job categories for Geometric Deep Learning jobs in Massachusetts are:

Geometric Deep Learning jobs near you

HMS - Postdoctoral Fellow in Zitnik Lab

Harvard University

Cambridge, MA • On-site

$54K - $73K/yr

Full-time

Re-posted 19 days ago

Harvard University rating

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Company rating: 8.5 out of 10

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Job description

Position
Details
Title
HMS - Postdoctoral Fellow in Zitnik Lab
School
Harvard Medical School
Department/Area
Position Description
We invite applicants for a postdoctoral fellow position in the Zitnik lab at Harvard Medical School in Boston, Massachusetts. The work of the Zitnik lab is focused on Artificial Intelligence for Medicine and Science.
The selected candidates will lead research in generative, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale
knowledge graphs, and large language models. Fellows will also have the opportunity to apply these methods to address challenges in scientific discovery and precision medicine.
We seek highly motivated applicants with a background in one or more of the following areas: agentic AI, geometric deep learning, large-scale knowledge graphs, large language models, multimodal learning, and generative AI. Successful applicants will be strong technically as well as have an inclination towards real-world problems. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals.
Salary and Benefits
This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post-PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines.
With this appointment, you are represented by the Harvard Academic Workers (HAW) - UAW for purposes of collective bargaining and matters affecting your compensation and working conditions.
Basic Qualifications
  • Ph.D. or M.D./Ph.D. in areas such as machine learning, computer science or closely related field.
  • Excellent programming skills and practical experience with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required.

Additional Qualifications
  • Experience in applications of AI to biology and medicine is a strong plus.

If visa sponsorship is needed, Harvard retains the discretion to determine which visa status is appropriate and whether a visa sponsorship application will ultimately be submitted, including payment of any applicable fees.
Special Instructions
The position is available immediately and can be renewed annually. Interested applicants should submit the following documents via email to Prof. Zitnik and use the subject line "Postdoctoral Research Fellows in Generative, Multimodal, and Agentic AI":
Curriculum Vitae (include links to your academic webpage and GitHub repositories for methods you developed)Three representative publications (preprints are acceptable)Statement of research (two pages) describing prior research experience and future research plan Contacts for three letters of recommendation (the letters will be solicited after the initial review)We are currently reviewing applications. Interested candidates are encouraged to submit their applications early.
With this appointment, you are represented by the Harvard Academic Workers (HAW) - UAW for purposes of collective bargaining and matters affecting your compensation and working conditions.
Contact Information
Heather Viana
Contact Email
heather_viana@hms.harvard.edu
Salary Range
Information regarding postdoctoral fellow salary, which is determined by the number of years post-PhD, can be found at https://postdoc.hms.harvard.edu/guidelines.
Minimum Number of References Required
Maximum Number of References Allowed
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