PhD in AI-driven calibration of Analog-to-Digital converters
PhD in AI-driven calibration of Analog-to-Digital converters
In the last 40 years, the systematic downscaling of CMOS Integrated Circuit (IC) technologies has enabled unprecedented improvements in the transistor density, frequency of operation, energy efficiency and reliability. Most recent CMOS technologies allow the integration of several billions of transistors in a digital microprocessor chip the size of a fingernail. While technology downscaling has been extremely beneficial for digital circuits, the design of analog frontend electronics and Analog-to-Digital Converters (ADCs) in deep sub-micron CMOS technologies is becoming increasingly challenging due to the systematic power supply reduction, the intrinsically larger device parameter variability, and the higher low-frequency noise level of these transistors. To achieve high performance while ensuring a high level of reliability, complex and accurate calibration circuits need to be added to the ICs to counteract these effects. However, the design of these calibration circuits is challenging, and their effectiveness is typically limited to specific operating conditions.
This project is done in cooperation with NXP semiconductors, Eindhoven.
As a PhD researcher from the Integrated Circuits group, you will investigate a novel methodology to design and implement calibration techniques for Analog-to-Digital Converters with the aid of Machine Learning (ML). During your PhD you will first identify the root causes which limit ADC performance. Next you will investigate suitable ML algorithms to correct these errors, calibrate the ADC behavior and improve its performance. Finally, you will design a novel ADC with embedded ML calibration circuits, achieving beyond state-of-the-art performance.
In summary your main tasks will be:
- Analyze and identify the major root causes which limit the performance of specific state-of-the-art ADCs.
- Explore new design methodologies to post-correct errors in ADCs and enable smart calibrations using Machine Learning.
- Investigate methods to efficiently train the ML algorithms using a reduced set of data points.
- Demonstrate the potential and effectiveness of the proposed approach by designing, implementing and characterizing Analog-to-Digital Converters achieving a performance beyond current state-of-the-art.
- Dissemination of the results of your research in international and peer-reviewed journals and conferences.
- Get involved in educational tasks such as the supervision of Master/Bachelor students and internships.
- Writing a dissertation based on the research outcomes and successfully defending it.
- max. 38 hours per week
- Eindhoven View on Google Maps
Eindhoven University of Technology (TU/e)
We are looking for a candidate who meets the following requirements:
- You have a strong background in mixed-signal Integrated Circuit (IC) design.
- You have a solid understanding of Analog-to-Digital Converters.
- You hold an MSc degree in Electrical Engineering.
- You are a talented and enthusiastic young researcher.
- Prior knowledge of machine learning algorithms, neural and/or Bayesian networks is a plus.
- You have good programming skills (preferably Python or MATLAB).
- You have good communication skills and can work in a multidisciplinary team.
You will need to have a good proficiency in spoken and written English; knowledge of Dutch is not required.
Conditions of employment
- A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
- A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
- To develop your teaching skills, you will spend up to 10% of your employment on teaching tasks.
- To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students.
- At TU/e we challenge you to take charge of your own learning process .
- A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
- Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
- Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
- A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
- Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
Eindhoven University of Technology (TU/e) is one of Europe's leading research universities. The Eindhoven area, in the southern part of the Netherlands, is one of Europe's top 'innovation ecosystems', with many high-tech companies and institutes. TU/e is intertwined with many of these companies and institutes, and research at TU/e is characterized by a combination of academic excellence, industrial relevance and societal interweaving.
Please visit www.tue.nl/jobs to find out more about working at TU/e!
We are an inclusive university community. Diversity is one of our most important values. We believe that engaging in international activities and welcoming students and staff from a wide variety of backgrounds enhances the quality of our education and research. We are always looking for people who can enrich our world with their own unique perspectives and experiences.
Do you recognize yourself in this profile and would you like to know more? Please contact
dr.ir. Marco Fattori, M.Fattori[at]tue.nl or dr.ir. Pieter Harpe, P.J.A.Harpe[at]tue.nl.
Further information about the employment conditions can be found here .
We invite you to submit a complete application by using the 'apply now'-button on this page.
The application should include:
- A cover letter explaining your motivation and suitability for the position.
- A list of courses and grades from your Master's programme.
- A detailed curriculum vitae.
- A scientific report in English, written by yourself (e.g. MSc thesis, traineeship report or scientific paper).
- Two references (name, affiliation, and contact information).
We look forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled.
Please keep in mind you can upload only 5 documents up to 2 MB each. If necessary, please combine files.
We do not respond to applications that are sent to us in a different way.
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