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Position: Doctoral Candidate (PhD Position) in 3D Computer Vision
Institution: University of Luxembourg
Location: Luxembourg City, Luxembourg
Duties: Carrying out research in a predefined topic and producing results; Disseminating results through scientific publications and/or patents; Providing support in setting-up and running experiments; Proposing and implementing real-time solutions; Participating in proposal writing; Participating in organizing relevant workshops and demonstrations
Requirements: A master’s degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field; Strong background in image/signal processing and in particular 3D computer vision; Strong programming skills in Python/C/C; Familiarity with machine learning and deep learning concepts; Experience with at least one of the following deep learning frameworks: TensorFlow, PyTorch, Keras, etc; Experience with relevant libraries for 3D mesh and point cloud analysis; Strong background in Applied Mathematics; A particular interest for 3D CAD modelling; Commitment, team working and a critical mind; Fluent written and verbal communication skills in English are mandatory
   
Text: UOL03834 31-Dec-2099 About the SnT SnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We’re looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you’ve come to the right place! Your Role We offer two attractive PhD candidate positions in close cooperation with our industrial partner Artec3D . Artec3D is a global leader in handheld and portable 3D scanners and has been at the forefront of developing innovative 3D technology since 2007 ( www.artec3d.com ). The successful candidates will join the Computer Vision, Imaging and machine Intelligence (CVI²) research group ( http://cvi2.uni.lu ) headed by Prof. Djamila Aouada to pursue a PhD in the field of 3D Computer Vision. They will carry out research in predefined topics contributing to SnT and Artec3D R&D activities. These positions will require conducting full scale research, starting from reviewing state-of-art methods through real-time implementation, and experimental validation. The position holders will be required to perform the following tasks: Carrying out research in a predefined topic and producing results. Disseminating results through scientific publications and/or patents Providing support in setting-up and running experiments Proposing and implementing real-time solutions Participating in proposal writing Participating in organizing relevant workshops and demonstrations Your Profile A master’s degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field Strong background in image/signal processing and in particular 3D computer vision Strong programming skills in Python/C/C Familiarity with machine learning and deep learning concepts Experience with at least one of the following deep learning frameworks: TensorFlow, PyTorch, Keras, etc. Experience with relevant libraries for 3D mesh and point cloud analysis Strong background in Applied Mathematics A particular interest for 3D CAD modelling Commitment, team working and a critical mind Fluent written and verbal communication skills in English are mandatory Here’s what awaits you at SnT A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT researchers, giving you solid guidance Exciting infrastructures and unique labs. At SnT’s two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 45 industry partners Multiple funding sources for your ideas . The University supports researchers to acquire funding from national, European and private sources Competitive salary package . The University offers a 12 month-salary package, over six weeks of paid time off, health insurance and subsidised living and eating Be part of a multicultural family . At SnT we have more than 60 nationalities. Throughout the year, we organise team-building events, networking activities and more But wait, there’s more! Complete picture of the perks we offer Discover our Partnership Programme Download the brochure: Why choose SnT for your PhD? Students can take advantage of several opportunities for growth and career development, from free language classes to career resources and extracurricular activities. In Short Contract Type: Fixed Term Contract 36 Month Work Hours: Full Time 40.0 Hours per Week Location: Kirchberg Job Reference: UOL03834 Further Information Applications should be submitted online and include: A full Curriculum Vitae List of three referees, including details (name, email address, etc.) Publication list, if any Transcript of all modules and results from university-level courses taken Research statement and topics of particular interest to the candidate (300 words) Preferably, a Github/Gitlab webpage listing completed projects in Computer Vision All qualified individuals are encouraged to apply. Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered. The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff. About the University of Luxembourg The University of Luxembourg aspires to be one of Europe’s most highly regarded universities with a distinctly international and interdisciplinary character . It fosters the cross-fertilisation of research and teaching , is relevant to its country, is known worldwide for its research and teaching in targeted areas, and is establishing itself as an innovative model for contemporary European Higher Education. The University`s core asset is its well-connected world-class academic staff which will attract the most motivated, talented and creative students and young researchers who will learn to enjoy taking up challenges and develop into visionary thinkers able to shape society. Further information For further information you may check: www.securityandtrust.lu or contact Djamila.Aouada@uni.lu
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