Design and develop advanced deep learning algorithms and models.
Optimize models for maximum performance, scalability, and efficiency.
Collaborate with cross-functional teams to integrate AI solutions.
Optimize models for maximum performance, scalability, and efficiency.
Collaborate with cross-functional teams to integrate AI solutions.
Requirements:
Masters or PhD in Biomedical Engineering, Computer Science, Electrical Engineering, or
a related field.
Background in Deep Learning theory, and track record of publications at conferences
such as CVPR, ICML, NIPS, ICCV, ECCV, and others
Proven track record of developing and successfully implementing deep learning models
for business applications.
Proven Statistical Analysis, Mathematical, and Problem-Solving skills.
Ability to thrive in a fast-paced, innovative environment.
Excellent communication skills with the ability to work collaboratively in a team
Masters or PhD in Biomedical Engineering, Computer Science, Electrical Engineering, or
a related field.
Background in Deep Learning theory, and track record of publications at conferences
such as CVPR, ICML, NIPS, ICCV, ECCV, and others
Proven track record of developing and successfully implementing deep learning models
for business applications.
Proven Statistical Analysis, Mathematical, and Problem-Solving skills.
Ability to thrive in a fast-paced, innovative environment.
Excellent communication skills with the ability to work collaboratively in a team
Deep Learning: Expertise in neural network architectures and training techniques.
Multivariate Time Series Analysis: Ability to handle and interpret complex temporal data.
data Analysis: Proficient in extracting insights from large datasets.
Computational Neuroscience: Understanding of brain-inspired algorithms and models.
This position is open to all candidates.
