Overview
The HuMaLearn team is currently offering two postdoctoral positions in the fields of Machine Learning (ML) and Deep Learning (DL). These roles present a significant opportunity for researchers looking to advance their careers in AI, particularly in innovative and impactful areas of study.
Background & Relevance
Machine Learning and Deep Learning are rapidly evolving fields that play a crucial role in various applications, from energy efficiency to predictive modeling in astrophysics. The significance of these areas is underscored by their potential to solve complex problems and enhance our understanding of both artificial intelligence and real-world phenomena. The research conducted in these domains not only contributes to academic knowledge but also has practical implications across industries.
Key Details
- Positions Available: 2 postdoctoral roles
- Expected Start Date: October
- Duration:
- First Position: 2 years, with topics to be determined, including but not limited to energy-efficient deep learning, trustworthiness of sequential deep neural networks (DNNs), interaction in ML/DL, and the Rashomon effect.
- Second Position: 1 year, focusing on a project related to the stability prediction of extrasolar systems using deep learning techniques.
- Application Links:
- First Position Details
- Second Position Details
Eligibility & Participation
These positions are aimed at researchers with a strong background in machine learning and deep learning. Candidates interested in exploring innovative research topics in these fields are encouraged to apply or share this opportunity with potential candidates.
Submission or Application Guidelines
Interested applicants should carefully review the details provided in the links above. To apply, candidates should reach out directly via email to express their interest and provide any necessary documentation as outlined in the job postings.
More Information
The research conducted in these postdoctoral positions will contribute to the broader AI/ML community by addressing critical challenges and exploring new frontiers in machine learning applications. The focus on topics such as energy efficiency and extrasolar systems stability highlights the interdisciplinary nature of current AI research, bridging gaps between technology and scientific inquiry.
Conclusion
This is a valuable opportunity for researchers looking to make significant contributions to the fields of machine learning and deep learning. Interested individuals are encouraged to apply or share this information with colleagues who may be interested in these exciting postdoctoral positions.
Category: PhD & Postdoc Positions
Tags: machine learning, deep learning, postdoc, HuMaLearn, extrasolar systems, DNNs, energy-efficient DL, Rashomon effect, research, AI, data science
