Senior Deep Learning Scientist

DeepRec.ai; New Haven (CT); On-site; USD 160,000 - 250,000; Full time

Job summary

A cutting-edge biotech startup is seeking a Senior Deep Learning Scientist to revolutionize the understanding of neurological diseases through innovative AI models. This role involves designing deep learning architectures tailored to complex biological data, optimizing models for high-performance environments, and collaborating with interdisciplinary teams. The ideal candidate will hold a Ph.D. in a related field with significant deep learning experience. This position offers a competitive salary ranging from $160,000 to $250,000 and is onsite in New Haven, Connecticut.

Qualifications

• Strong demonstrated track record of applying deep learning to biological problems.
• Ability to translate conceptual research frameworks into deployable architectures.
• Comfort working across research and applied implementation.

Responsibilities

• Design, develop, and deploy state-of-the-art deep learning models for analyzing multi-modal biological data.
• Work closely with interdisciplinary teams to integrate multi-modal datasets.
• Publish research findings and present at scientific conferences.

Skills

Experience with GNNs

Expertise in PyTorch

Familiarity with cloud computing

Experience in high-performance computing

Research and implement deep learning architectures

Education

PhD or Post-doc in Computer Science or related STEM field

Job description

Overview

Senior Deep Learning Scientist opportunity at a cutting-edge biotech startup focused on a first-of-its-kind platform to conduct preclinical studies and advance understanding of neurological diseases.

Base pay range

$160,000.00/yr - $250,000.00/yr

Location and employment

Onsite – New Haven, Connecticut

Application note

Direct message the job poster from DeepRec.ai. Apply now or reach out to Ben at [e-mail] to learn more.

Senior Deep Learning Scientist

Senior Deep Learning Scientist
$160,000 - $250,000
Onsite – New Haven, Connecticut

A cutting-edge biotech startup is seeking a Senior Deep Learning Scientist to join their team. This innovative company is pioneering a first-of-its-kind platform to conduct preclinical studies, aiming to revolutionize the understanding and treatment of neurological diseases.

As a Senior Deep Learning Scientist, you will play a pivotal role in designing and implementing AI models that integrate complex biological signals. You will be at the forefront of pioneering work in areas such as generative graph representation learning, contributing to the development of novel AI architectures tailored to the intricacies of human brain biology.

Key Responsibilities

• Design, develop, and deploy state-of-the-art deep learning models for analyzing multi-modal biological data.


• Develop deep learning architectures incorporating biological inductive biases, and explore generative graph representation learning to uncover novel patterns in brain data.


• Work closely with bioinformatics, experimental biology, and engineering teams to integrate multi-modal datasets into cohesive AI frameworks.


• Optimize deep learning pipelines for petabyte-scale datasets and ensure models are scalable on high-performance computing infrastructures.


• Publish research findings and present at scientific conferences to contribute to the broader AI and biomedical communities.

Requirements

• PhD or Post-doc in Computer Science, Machine Learning, or a related STEM field with a strong demonstrated track record of applying deep learning to biological problems.


• The ability to translate conceptual research frameworks into deployable architectures.


• Comfort working across research and applied implementation.


• Proven experience with GNNs and an ability to tailor these methods to biological data. Experience with generative graph representation learning is a significant plus.


• Expertise in PyTorch with the ability to build and deploy scalable models.


• Familiarity with developing production-quality pipelines, cloud computing, and model deployment best practices.


• Demonstrated ability to research and implement novel deep learning architectures tailored to complex biological datasets.


• Experience with high-performance computing (HPC) environments or distributed training techniques for large-scale GNN models.

Seniority level

• Not Applicable

Employment type

• Full-time

Job function

• Science

Industries

• Data Infrastructure and Analytics


• Software Development

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