Job description
Job summary
An exciting opportunity has arisen for a Research Associate to work under the direction of Dr Stefanos Zafeiriou and Dr Tolga Birdal.
The main aim of the project is to investigate the mechanisms of modern artificial intelligence algorithms, particularly deep neural networks. The project will combine cutting edge research on deep learning, statistical learning theory, and non-Euclidean machine learning to help develop next-generation machine learning methodologies that are not only high-performing and efficient, but are also robust and reliable in novel contexts, and are guided by sound inductive biases. Application areas of immediate interest include computer vision, natural language processing, 3D vision, neuroscience, computational biology, and related fields.
Imperial College is consistently in the top 10-world university ranking. The College achieved second place in the Complete University Guide's Computer Science subject table for 2017. The Department of Computing has repeatedly been awarded the highest research ratings in the REF assessments, was ranked 1st in the Research Intensity table published by The Times Higher and was rated as "Excellent" in the most recent national assessment of teaching quality.
Duties and responsibilities
Within the project, the Research Associate will be expected to work on predictive and generative models, as well as models with inputs that are structured to varying degrees (e.g. images, sets, graphs, text). The applicant is expected to have a strong publication record in top conferences and journals of machine learning and its application domains (NeurIPS, CVPR, ICCV, ICML, TPAMI, Nature & Science research journals etc).
Essential requirements
• A MSc degree in a computing or related field, or equivalent
• A track record of publications in excellent venues such as (NeurIPS, CVPR, ICCV, ICML, ECCV, TPAMI, etc.)
• A strong background in maths
• Research background in machine learning fundamentals such as tensor methods, graphical models, and probabilistic inference.
• Teaching experience in machine learning or related fields.
• Knowledge in one or more of the following areas: machine learning, computer vision, geometry processing, statistical learning theory.
• Competence in deep learning (including programming proficiency in frameworks such as PyTorch or TensorFlow).
Please see job description for a full list of requirements.
Further information
In addition to completing the online application candidate should attach.
• A full CV, with a list of publications
• A 2-page research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.
Informal enquiries related to the position should be directed to Dr Tolga Birdal: t.birdal@imperial.ac.uk
For queries regarding the application process contact Jamie Perrins: j.perrins@imperial.ac.uk
About Imperial College London
Imperial College London is the UK's only university focussed entirely on science, engineering, medicine and business and we are consistently rated in the top 10 universities in the world.
You will find our main London campus in South Kensington, with our hospital campuses located nearby in West and North London. We also have Silwood Park in Berkshire and state-of-the-art facilities in development at our major new campus in White City.
We work in a multidisciplinary and diverse community for education, research, translation and commercialisation, harnessing science and innovation to tackle the big global challenges our complex world faces.
It's our mission to achieve enduring excellence in all that we do for the benefit of society - and we are looking for the most talented people to help us get there.
Additional information
Please note that job descriptions cannot be exhaustive, and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.
Imperial College is committed to equality of opportunity and to eliminating discrimination. All employees are expected to follow the Imperial Values & Behaviours framework . Our values are:
• Respect
• Collaboration
• Excellence
• Integrity
• Innovation
In addition to the above, employees are required to observe and comply with all College policies and regulations.
We are committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment for all. We therefore encourage candidates to apply irrespective of age, disability, marriage or civil partnership status, pregnancy or maternity, race, religion and belief, gender reassignment, sex, or sexual orientation. We are an Athena SWAN Silver Award winner, a Disability Confident Leader and a Stonewall Diversity Champion.
For technical issues when applying online please email support.jobs@imperial.ac.uk
