沙特阿卜杜拉国王科技大学机器学习博士后

沙特阿卜杜拉国王科技大学机器学习博士后

阿卜杜拉国王科技大学（King Abdullah University of Science & Technology），简称KAUST，位于沙特阿拉伯西海岸吉达。是一所提供研究生课程的研究型大学，也是沙特境内第一所男女共校的大学。学校采取“小而精”的办学模式，专攻理工领域，仅招收硕士与博士研究生。

Postdoc in Machine Learning

King Abdullah University of Science and Technology

King Abdullah University of Science and Technology: Postdoc Positions:

Biological and Environmental Science and Engineering Division (postdoc)

Location

Thuwal, Saudi Arabia

Open Date

Jan 25, 2023

Description

The Machine Learning (ML) group led by Professor Ricardo Henao at KAUST (King Abdullah University of Science and Technology) has multiple openings for Postdoctoral level positions to conduct research in the field of machine learning, more specifically, deep learning and representation learning architectures. Application areas of ML include, but are not limited to, computer vision, natural language processing, computational biology and healthcare.

Our group focuses on important and fundamental open problems in machine learning research and challenging applications in diverse fields ( e.g. , biology and healthcare) where deep learning architectures, hierarchical learning models and representation learning can be truly impactful. The group strives to publish in top-tier ML venues such as NeurIPS, ICLR, ICML, AISTATS, CVPR, ICCV, ACL, EMNLP, etc. Our group is embedded in the BESE (Biological and Environmental Science and Engineering) division, which supports and promotes a rich multi-disciplinary work environment. We are looking for like- minded scientists who are passionate about ML methodology and/or its potentially transformative applications in research and industry.

The positions are fully funded and for postdocs, initially available for up to three years with the possibility of renewal.

Qualifications

The positions are suited for recent PhD graduates in relevant quantitative fields ( e.g. , electrical engineering, computer science, statistics and data science), with evidence of research activity resulting in publications and presentations. Effective communication skills in English both in writing and presentation are key for dissemination purposes.

Advantageous skills:

Experience with computational frameworks for machine learning ( e.g. , PyTorch and TensorFlow).

Experience with high-performance computational environments (e.g., cloud and clusters).

Experience with handling large-scale datasets.

Solid background in statistics and probability theory.

Prior publications in top-tier ML venues (see examples above).

Application Instructions

Application should include:

Single page cover letter describing experience and research interests.

CV including a list of publications and previous machine learning experience.

Names and contact information for two references.

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