- From: Costabello, Luca <luca.costabello@accenture.com>
- Date: Fri, 6 Dec 2019 09:45:57 +0000
- To: "public-lod@w3.org" <public-lod@w3.org>, "semantic-web@w3.org" <semantic-web@w3.org>
- Message-ID: <ABE237FC-DAEF-4078-BC1A-9A183EC92E01@accenture.com>
Accenture Labs Dublin is looking for a Post-Doctoral researcher in the domain of Graph Representation Learning and Explainable AI. You will join a newly-created, multi-partner project whose goal is to identify factors that can cause development of new medical conditions, and worsen the quality of life of cancer survivors. The project will analyse patient’s clinical, genomic, behavioural data and existing open data in order to determine a follow-up adapted to the individual needs. The length of the PostDoc is 3 years. You will join our team of AI researchers and engineers, and work on research activities focused on explainable AI and machine learning on knowledge graphs. You will be in charge of designing, developing, evaluating, and applying novel models. That will include software development (including contributing to our open source stack [1]), carrying out experiments, and publishing results in academic venues. More precisely, you will design interpretable machine learning models to infer knowledge from a graph of clinical, genomic, and behavioural data. Explanations will use a wide range of techniques, such as rules derived from the deep learning models, interpretable machine learning, or graph-based explanations based on network analysis. # Requirements * PhD in computer science, statistics, mathematics or related field. * Proven communication skills (talks, presentations, academic publications) * Strong foundation in mathematics, statistics and probability * Strong knowledge of Machine Learning foundations * Knowledge of mainstream Deep Learning architectures * Ability to work creatively and analytically in a problem-solving environment * Strong Python programming skills * Hands-on experience with machine learning frameworks e.g. Scikit-learn, TensorFlow, PyTorch, and scientific Python (e.g. numpy) * Eagerness to contribute in a team-oriented environment # Preferred Qualifications * Experience with graph-based knowledge representation (e.g. knowledge graphs) * Familiarity with graph representation learning (e.g. knowledge graph embeddings, graph neural networks) * Experience with explainable AI or interpretable machine learning techniques * Working knowledge of Linux OS and shell scripting * Hands-on experience with git and issue tracking systems #About Accenture Labs Dublin Accenture Labs is a network of R&D labs distributed on seven locations worldwide, home of over 200 applied R&D experts. The Dublin Labs team focuses on artificial intelligence, with a strong emphasis on explainable AI, machine learning on knowledge graphs (graph representation learning), and computational creativity. The lab is co-located with the over 100 designers, developers and domain experts at The Dock, Accenture's newly-created global centre for innovation. We offer a blend of industrial-related applicative problems and academic-oriented activities, including an open publication policy. Apply online here: https://www.accenture.com/ie-en/careers/jobdetails?id=00784132_en or feel free to contact Luca Costabello should you have any questions [2]. [1] https://github.com/Accenture/AmpliGraph [2] https://luca.costabello.info/ ________________________________ This message is for the designated recipient only and may contain privileged, proprietary, or otherwise confidential information. If you have received it in error, please notify the sender immediately and delete the original. Any other use of the e-mail by you is prohibited. Where allowed by local law, electronic communications with Accenture and its affiliates, including e-mail and instant messaging (including content), may be scanned by our systems for the purposes of information security and assessment of internal compliance with Accenture policy. Your privacy is important to us. Accenture uses your personal data only in compliance with data protection laws. For further information on how Accenture processes your personal data, please see our privacy statement at https://www.accenture.com/us-en/privacy-policy. ______________________________________________________________________________________ www.accenture.com
Received on Friday, 6 December 2019 09:46:05 UTC