Student Assistant - Programming, Machine Learning and MLOps

Technical University of Denmark

Denmark

October 22, 2021

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Student Assistant - Programming, Machine Learning and MLOps

DTU Compute

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Thursday 07 Oct 21

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Apply no later than 22 October 2021 Apply for the job at DTU Compute by completing the following form.

We are looking for a talented student to work on deployment of machine learning models.

The job LiRA (Live Road Assessment) is a project which aims to use Machine Learning to predict road conditions based on the data collected from various sensors installed in vehicles. Your main responsibility will be to develop, implement, and document software components that will be used for deployment of machine learning models.

Our expectations of you We are looking for a student assistant who has interest in machine learning deployment with documented experience in Python, Docker and understanding of machine learning lifecycle. Previous experience with deployment of machine learning models is an advantage. You should be used to working independently, be strong in detail and also have very good English skills.

What we offer in return We offer a challenging and independent student job where you will in the central part of developing components for machine learning deployment. You will have insight into the entire research project. and into the process of conducting multi-disciplinary international research at DTU and in collaboration with other international universities. We offer flexible working hours (especially around exams).

Salary and appointment terms The appointment will be based on the collective agreement for student lecturers at universities etc. (SUL). Working hours are on average 10 hours per week and can be organized flexibly in relation to holidays, exams, etc. Starting date is 1 November 2021 (or according to mutual agreement). The employment runs as long as you are an active student.

The workplace is DTU Lyngby Campus.

Application and contact Please submit your online application no later than Friday, 22 October 2021 (Danish time). You can apply for the position online at www. career.dtu.dk. Open the “Apply online” link, fill out the form and attach your motivated application, CV and documentation for study activity. In the application, we would like to hear a little about you, your competencies and why you are applying for the position.

If you would like additional information about the position, please contact postdoc Milena Bajic at e-mail: mibaj@dtu.dk. Read more about LiRA prject at https:// lira-project.dk/.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Compute DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. At DTU Compute we believe in a diverse workplace with a flexible work-life balance.

Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN's 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,900 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

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