About this role
<p><br><img style="width:930.0px;height:205.0px" src="https://performancemanager5.successfactors.eu/OSRAMP/ams_OSRAM_RCM.jpg"></p> <p> </p> <p style="color:#fd5000">Sense the power of light</p> <p style="text-align:justify"><br>The ams OSRAM Group is a global leader in innovative light and sensor solutions. With more than 110 years of industry experience, we combine engineering excellence and global manufacturing with a passion for cutting-edge innovation enabling transformative advancements in the automotive, industrial, medical, and consumer industries. “Sense the power of light” – our success is based on the deep understanding of the potential of light and distinct portfolio of emitter and sensor technologies. Around 19,700 employees worldwide drive innovations alongside societal megatrends.<br>Find out more about us on <a href="https://ams-osram.com">https://ams-osram.com</a></p> <p style="text-align:justify"> </p> <p style="text-align:justify">The CSA division supplies sensors that bridge the gap between the world we live in and the digital world of machines. By converting physical signals - heartbeats, sounds, light waves - into data, we enable robots, cars and other devices to interact with people and improve our world. What drives CSA is a relentless desire to contribute to technology and have a meaningful impact on the world. This business thrives on solving complex problems and partnering with global leaders at the forefront of technological advancement. Our goal: to push the boundaries of sensor technology and empower innovators to make the world smarter, healthier and happier.</p> <p style="text-align:justify"><br><span style="color:#fd5000">Your new responsibilities</span></p><p>Theoretical Part:<br>• Get an understanding of what defect data is and how it can be handled.<br>• Comprehensive literature review of state of the art usage of defect data within semiconductor industry (yield prediction, signature prediction, defect classification etc.).<br>• Literature review of possibly already existing models incorporating defect data.<br>• Evaluation of approaches to establish yield predictions with defect data</p> <p>Practical Part:<br>• Close cooperation with various departments (Defect, IT, Product Engineering etc.)<br>• Understand defect classification/categorization<br>• Get actual state of available data and its usage<br>• Define possible solutions for the problem statement</p><p><br><span style="color:#fd5000">Who we are looking for</span></p> <p><br><p>• Completed Bachelor’s degree in data science or comparable<br>• Experience in Machine Learning and/or Artificial Intelligence<br>• Experience in semiconductor environment beneficial<br>• Independent and structured way of working</p> <p>We offer competitive salaries and additional benefits based on your performance, experience, and qualifications. Employment is in accordance with the collective agreement for the electrical and electronics industry, employment group E (<a href="https://www.feei.at/aktuelles/mindestloehne-und-gehaelter-eei/)">https://www.feei.at/aktuelles/mindestloehne-und-gehaelter-eei/)</a>.</p></p> <p><br>Please contact <strong>Marlies Nigitz</strong> for further information via <strong><a href="mailto:[email protected]">[email protected]</a></strong> or <strong>+43 (3136) 50032853</strong>.</p>