Doctoral student in Mathematics with focus on Machine Learning and Computer Vision - Hiring in process/Finished, not possible to apply

Research subject
Mathematics

Job assignment
The recent development of computer vision, machine learning and robotics has been significant but fundamental advances are still necessary in order to integrate the technologies into a functional high-performance system that can lead in the long run, to a truly autonomous robot. In this interdisciplinary project entitled Learning to See in a Dynamic World, funded in part by an European research Council Consolidator Grant, our goal is to fundamentally advance the methodology of computer vision by exploiting a dynamic analysis perspective in order to acquire accurate, yet tractable models that can automatically learn to sense our visual world, localize still and animate objects (e.g. chairs, phones, computers, bicycles or cars, people and animals), actions and interactions, as well as qualitative geometrical and physical scene properties, by propagating and consolidating temporal information, with minimal system training and supervision. Within this framework up to several doctoral positions are available in computer vision (scene understanding with emphasis on visual recognition) or machine learning (largescale optimization, structured prediction using deep learning, as well as deep reinforcement learning and weakly supervised learning) within the Computer Vision and Machine Learning Group in the Faculty of Engineering, Department of Mathematical Sciences at Lund University (http://www.maths.lth.se/people/math-csu/). The group performs world-class research in computer vision and machine learning and has ongoing collaborations with researchers at the University of California at Berkeley, University of Toronto, INRIA, Google Deep Mind and Google Research.

The position also includes some instruction in basic mathematics education at university level.

Eligibility
Students with basic eligibility for third-cycle studies are those who- have completed a second-cycle degree- have completed courses of at least 240 credits, of which at least 60 credits are from second-cycle courses, or- have acquired largely equivalent knowledge in some other way, in Sweden or abroad. It is also required that the student has achieved a level of knowledge in mathematics that corresponds to that of Master of Science programs in Engineering Mathematics or Engineering Physics.

The employment of doctoral students is regulated in the Swedish Code of Statues 1998: 80. Only those who are or have been admitted to PhD-studies may be appointed to doctoral studentships. When an appointment to a doctoral studentship is made, the ability of the student to benefit from PhD-studies shall primarily be taken into account. In addition to devoting themselves to their studies, those appointed to doctoral studentships may be required to work with educational tasks, research and administration, in accordance with specific regulations in the ordinance.

Basis of Assessment
The doctoral candidates should have a strong mathematical background and excellent grades. A record of prior research or prizes in science or computing contests and/or experience in computer vision or machine learning is a plus. Good English language skills are required. The candidates are expected to develop their own ideas and communicate scientific results orally as well as in written form.

Besides detailed CV, statement of purpose, and complete academic record,  the candidate should include one of his/her relevant work such as a bachelor's or master's thesis (or outline of a thesis under preparation) or an article. Incomplete applications will not be considered.

Type of employment
Limit of tenure, four years according to HF 5 kap 7§.