This PhD thesis focuses on advancing non-destructive testing methods for enhanced data acquisition and processing in materials and production processes. 
State-of-the-art optical (including infrared and terahertz radiation) and acoustic (including ultrasound) sensor technologies will be explored to obtain detailed insights without causing harm to materials. 
The integration and combination of innovative signal processing and machine learning methods such as Compressive Sensing, Super-Resolution Imaging, and Deep Neural Networks will be crucial in enhancing data extraction and analysis. 
Acoustic techniques like laser ultrasound and photo acoustics for imaging internal structures will be investigated, while also investigating methods to counteract attenuation, thus enhancing spatial resolution. 
Overall, the goal is to revolutionize the characterization of materials and processes by exploring innovative sensor technologies and advanced signal processing and machine learning methods. 

Working in a team with close links to international academic partners and national industry, you will be responsible for the following tasks:

• Developing machine learning or deep learning based algorithms to analyse arbitrary data, such as image, audio or radar data. 
• Designing experiments to thoroughly evaluate and compare the performance of multiple algorithms, including identifying potential weaknesses. 
• Publish results in peer-reviewed international conferences and journals. 
• Execute and manage industrial projects in collaboration with other team members.

Would you like to work in an international team environment at the forefront of future communication systems? Do you have the following skills, education and/or work experience (the more the better)? 

• Master's degree in Computer Science or related fields such as Statistics, Mathematics, Mechatronics or Physics. 
• Strong understanding and experience in machine learning, data science and signal processing. 
• Attention to detail and strong analytical and problem-solving skills. 
• Proficiency in Python and ML libraries such as sklearn, Pytorch, Pandas, numpy, etc.. 
• Solid software engineering skills in OOD, OOP, git, and more.
• Excellent written and oral communication skills in English.
• Team player, self-motivated and goal-oriented.
• Enthusiasm for developing new ideas and a positive attitude towards new challenges. 

• Application deadline: 3 November 2024
• Weekly working hours: 38.5
• Diversified research activities with plenty of technical challenges.
• State-of-the-art lab facilities and instruments.
• Internal and external training opportunities for further development.
• Home Office possible.
• € 4 per day food allowance in restaurants or € 2 per day in supermarkets.
• Family & kids friendly.
• Free coffee/milk/tea & fresh fruits.

For this position you will receive a monthly gross salary of EUR 3,827, which will be paid 14 times a year. Financial support for housing for stays abroad (e.g., in case of secondments) and travelling expenses will be offered on a case-by-case basis.

Silicon Austria Labs (SAL) is a top research center for Electronics and Software Based Systems (ESBS). At three locations (Graz, Villach, Linz), SAL is conducting research along the entire ESBS value chain in the areas of sensor systems, power electronics, intelligent wireless systems, microsystems and embedded systems to develop future-oriented solutions for industrial production, health, energy, mobility, safety and more. SAL brings together key players from industry, science and research and thus valuable expertise and know-how and conducts cooperative, application-oriented research along the value chain. Cooperative projects are co-financed by SAL and enable a fast and unbureaucratic project start. SAL is thus shaping the high-tech location Austria and Europe and developing the future