Deep Learning Research Asociate, Qualcomm AI Research
Informatics Institute – Qualcomm AI Research
Publication date 19 October 2018
Level of education University
Salary indication Competitive compensation package
Closing date 16 December 2018
Hours 38 hours per week
Vacancy number 18-634
Qualcomm AI Research and the University of Amsterdam have teamed up to offer a novel Research Associate PhD position. This position is aimed at talented researchers with a master's degree in computer science or related field. The Research Associate will work closely with Prof. Max Welling, Taco Cohen, and others at our Amsterdam office to plan, perform and publish high quality research in deep learning.
The position combines the advantages of being an employee at Qualcomm as well as being a guest PhD student in the QUVA Lab at the University of Amsterdam:
- permanent position at Qualcomm with a competitive compensation package;
- freedom to set your own research agenda within the broad scope of the lab, and subject to approval by your academic supervisor(s);
- interact with and learn from research & product teams in Qualcomm offices around the globe;
- interact with and learn from members of one of the best academic ML research labs in the world;
- publish at top conferences and journals;
- have your research rapidly incorporated into products used by billions of people;
- use our deep learning compute cluster;
- write a thesis and obtain a PhD degree from the University of Amsterdam, with Prof. Max Welling as your promotor.
You will work in the Qualcomm AI Research group located on the University of Amsterdam campus, and have the ability to collaborate with other PhD students in the QUVA lab (Qualcomm-UvA). QUVA is part of AMLAB, a machine learning research group at the University of Amsterdam consisting of around 50 members including professors, postdocs, and PhD students. AMLAB's research focus is on deep learning and large-scale graphical models, causality, reinforcement learning, and explainable AI. The candidate is expected to participate in limited teaching activities at the University of Amsterdam.
Your R&D work might include development of new methods in the following areas:
- model compression and efficient computation techniques for speed and power efficiency;
- data compression and deep generative models (VAEs, GANs, Autoregressive models);
- equivariant networks for data-efficient deep learning;
- bayesian deep learning for mission-critical risk assessment;
- adversarial learning for robustness;
- reinforcement learning for behavioral planning and resource management;
- active learning on massive datasets;
- training on low-power edge devices for personalization and privacy
Requirements Minimum Qualifications:
- Master's degree in computer science, physics, mathematics, or a related field;
- knowledge of basic mathematics (linear algebra, calculus, probability) and programming;
- knowledge of machine learning fundamentals (overfitting & generalization, popular classification/regression/clustering methods, loss functions, Bayesian networks, EM / variational inference, kernel methods, etc.);
- experience in implementing and training deep networks.
- Track record of research excellence and high-quality publications;
- strong understanding of machine learning algorithms & principles, and numerical optimization;
- experience using machine learning toolboxes (e.g. PyTorch or TensorFlow);
- knowledge of application areas, such as computer vision or speech analysis;
- knowledge of advanced mathematics;
- strong software engineering skills.
Further information may be obtained from:
- Prof. Max Welling
Permanent position at Qualcomm AI Research with a competitive compensation package. Employment will be held at the Qualcomm AI Research which is located on the University of Amsterdam campus at Science Park Amsterdam.
Please contact Prof. Max Welling for more information.
Qualcomm is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
You may only submit your application by electronic mail using the link below. To process your application immediately, please quote vacancy number 18-634 in the subject line.
Your application must include:
- a curriculum vitae;
- a motivation letter that explains why you have chosen to apply for this specific position;
- a copy of your Master's thesis;
- a complete record of Bachelor and Master courses (including grade transcripts and the explanation of the grading system) and
- the names and contact information of two academic references (please do not include any recommendation letters).
All these should be grouped in a single PDF attachment. #LI-DNP
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