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Position: Machine Learning Engineer (f/m) in Deep Learning and Image Generation for Astrophysics
Institution: Zürcher Hochschule für Angewandte Wissenschaften
Location: Winterthur, Zürich, Switzerland
Duties: Design and implement image-to-image-translation generative models using deep learning (e.g., GANs, VAEs) in the context of astrophysical data (numerical simulations and radio observations); Collaborate with researchers from other institutions (e.g., UZH, FHNW, ETH, EPFL) within a Swiss-wide consortium to gather data and align processes and pipelines; Submit model training proposals and make use of high-performance computing facilities (e.g., Swiss Supercomputing Center CSCS); Participate actively in the consortium by shaping the role of the ZHAW in the SKA (Square Kilometer Array) consortium at national level and present outcomes of research at regular consortium meetings and conferences; Contribute to publication of research outcomes in scientific journals
Requirements: We are looking for a passionate and pragmatic person with ability and interest in applying Machine Learning in a scientific context. We expect a solid background in deep learning and software development, with a master's degree/PhD in computer science or a comparable background; You have proven competencies in the areas of computer science and software development (e.g., Python, C++, CUDA), as well as strong knowledge and experience with relevant deep learning software packages and tools (e.g., Pytorch, Tensorflow), specifically in the application to image processing/computer vision; Previous hands-on experience with generative models (e.g., GANs, VAEs) is a big plus, interest or experience in working with astrophysical data (numerical simulations/radio observations) is an advantage; You work independently, manage projects in autonomy and also enjoy cooperation in interdisciplinary and international project teams. You are creative in finding solutions for problems, you have an accurate, resultoriented working style and are fluent in English; In return, we offer a research engineer position, initially limited to December 2024, in which you will be able to work with state-of-the-art technology and infrastructure on a project of national visibility, enter a vibrant research community and visit other research institutes in CH. You will be able to access and train your models on our state-of-the-art computing infrastructure (4 NVIDIA DGX servers, > 60 Tesla and Titan GPUs), as well as on the cutting-edge computing infrastructure at CSCS (e.g., Alps)
   
Text: Machine Learning Engineer (f/m) in Deep Learning and Image Generation for Astrophysics 50 - 100 % With your experience in computer vision and as a solution-oriented person you contribute state-of-the-art algorithms to a challenging project of international relevance in the field of radio astronomy. School: School of Engineering Starting date: 01. June 2022 or by appointment Your role Design and implement image-to-image-translation generative models using deep learning (e.g., GANs, VAEs) in the context of astrophysical data (numerical simulations and radio observations) Collaborate with researchers from other institutions (e.g., UZH, FHNW, ETH, EPFL) within a Swiss-wide consortium to gather data and align processes and pipelines Submit model training proposals and make use of high-performance computing facilities (e.g., Swiss Supercomputing Center CSCS) Participate actively in the consortium by shaping the role of the ZHAW in the SKA (Square Kilometer Array) consortium at national level and present outcomes of research at regular consortium meetings and conferences Contribute to publication of research outcomes in scientific journals Your profile We are looking for a passionate and pragmatic person with ability and interest in applying Machine Learning in a scientific context. We expect a solid background in deep learning and software development, with a master's degree/PhD in computer science or a comparable background You have proven competencies in the areas of computer science and software development (e.g., Python, C++, CUDA), as well as strong knowledge and experience with relevant deep learning software packages and tools (e.g., Pytorch, Tensorflow), specifically in the application to image processing/computer vision Previous hands-on experience with generative models (e.g., GANs, VAEs) is a big plus, interest or experience in working with astrophysical data (numerical simulations/radio observations) is an advantage You work independently, manage projects in autonomy and also enjoy cooperation in interdisciplinary and international project teams. You are creative in finding solutions for problems, you have an accurate, resultoriented working style and are fluent in English In return, we offer a research engineer position, initially limited to December 2024, in which you will be able to work with state-of-the-art technology and infrastructure on a project of national visibility, enter a vibrant research community and visit other research institutes in CH. You will be able to access and train your models on our state-of-the-art computing infrastructure (4 NVIDIA DGX servers, > 60 Tesla and Titan GPUs), as well as on the cutting-edge computing infrastructure at CSCS (e.g., Alps) Jetzt online bewerben ­ This is what we stand for Zurich University of Applied Sciences ZHAW is one of Switzerland's largest multidisciplinary universities of applied sciences, with over 14'000 students and 3'400 faculty and staff. The , as one of the leading educational and research institutions in Switzerland, focuses on topics relevant to the future. 14 institutes and centres guarantee high-quality education, research and development with a focus on the areas of energy, mobility, information and health. The currently maintains two research groups in the fields of and and sees its growth areas in the key areas of as well as and . The CAI conducts method-oriented applied research and development at the highest level in the field of machine learning and is committed to a human-centered approach to artificial intelligence, thereby actively shaping the ethical dimension. Das dürfen Sie erwarten Wir bieten hochschulgerechte Arbeits- und Anstellungsbedingungen und fördern aktiv die Personalentwicklung unserer Mitarbeitenden und Führungspersonen. Eine detaillierte Beschreibung der Vorteile finden Sie auf der Seite . Hier die wichtigsten Eckpunkte: Contact Prof. Dr. Thilo Stadelmann Director of CAI Samanta Barreiro Recruiting Manager 2022-04-22 Temporary ZHAW Zürcher Hochschule für Angewandte Wissenschaften Winterthur Region of Winterthur/Schaffhausen 8401
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