Postdoctoral Researcher in Artificial Intelligence Position Available In Orleans, Louisiana
Tallo's Job Summary: The Postdoctoral Researcher in Artificial Intelligence at Tulane University in New Orleans, LA, will focus on cutting-edge AI methodologies. Responsibilities include developing advanced AI/ML models, evaluating model robustness, contributing to open-source libraries, and pursuing novel research directions. Qualifications include a Ph.D. in computer science or related field, expertise in transformer-based models, deep learning frameworks, GNNs, and reinforcement learning, as well as experience in data pipelines and cloud infrastructure.
Job Description
Postdoctoral Researcher in Artificial Intelligence
Tulane University
in New Orleans, LA
Apply Now Type:
Full-Time
Posted:
04/21/2025
Category:
Computer Science Tulane University:
Health Sciences:
Office of Research:
Bywater Institute Location:
Uptown Description:
Prof. Ibrahim Demir at the ByWater Institute, Tulane University is seeking a highly motivated Postdoctoral Researcher specializing in next-generation artificial intelligence (AI) methodologies. The successful candidate will be at the forefront of exploring cutting-edge techniques-such as multimodal multi-task transformer-based architectures, large-scale generative modeling, graph neural networks (GNNs), and reinforcement learning frameworks-for applications spanning environmental monitoring, decision support, and educational innovation. Responsibilities include developing and fine-tuning advanced AI/ML models, designing experiments to evaluate model robustness and bias, contributing to open-source libraries, and pursuing novel research directions that leverage interdisciplinary collaborations. Additionally, the postdoctoral researcher will play a pivotal role in securing competitive funding from agencies such as NSF and NIH, mentoring graduate students, disseminating findings in high-impact journals and conferences, and engaging with diverse stakeholders to translate AI breakthroughs into real-world impact.
Qualifications:
Applicants must have a Ph.D. in computer science, electrical/computer engineering, or a closely related field, with a focus on state-of-the-art machine learning and AI methods. Additionally, the ideal candidate will have: Demonstrable expertise in developing and training large-scale transformer-based models (e.g., GPT, BERT, ViTs) for multimodal (text, image, video, sensor data) and multi-task learning.
Proficiency in advanced deep learning frameworks (TensorFlow, PyTorch) for GPU-based, large-batch model training, including experience with distributed and parallel computing (e.g., multi-GPU or HPC cluster environments).
Familiarity with specialized AI domains such as GNNs, reinforcement learning (especially policy optimization or RLHF), and model fusion methodologies (e.g., cross-modal attention, late fusion, or hierarchical fusion strategies).
Hands-on experience with large-scale data pipelines, hyperparameter optimization, data augmentation, and model interpretability/visualization tools.
Working knowledge of high-level DevOps practices (Docker, Kubernetes, CI/CD) and cloud infrastructure (AWS, Azure, or others) for production deployment of AI systems.
A strong publication record, preferably in top-tier AI/ML venues (e.g., Neur
IPS, ICML, ICLR, CVPR, AAAI
) and relevant journals.
Emerging track record in leading grant proposals, project management, or collaborative research initiatives, with strong interpersonal and mentoring skills.
Enthusiasm for interdisciplinary and applied research, with the capacity to bridge AI advancements to different domains.
Application Instructions:
Please apply online via Interfolio. Applications must include CV, cover letter, and research statement. Apply Now
