Job
- Level
- Experienced
- Location
- Frankfurt (Oder)
- Working Model
- Hybrid, Onsite
- Job Field
- Data, Application
- Employment Type
- Full Time
- Contract Type
- Temporary employment
Job Summary
In this role, you will develop innovative machine learning methods for analyzing and predicting circuit reliability while collaborating with an interdisciplinary team on fundamental research questions.
Job Technologies
Your role in the team
- We are seeking a highly motivated PhD student to conduct research at the intersection of machine learning, electronic design automation (EDA), and electronic circuit reliability.
- The position is part of a three-year research project funded by the German Research Foundation (DFG). The project aims to develop novel machine-learning methods for the analysis and prediction of circuit reliability, with the goal of making reliability assessment more efficient, scalable, and suitable for increasingly complex electronic systems.
- The successful candidate will have the opportunity to investigate fundamental research questions and develop novel approaches using modern machine-learning techniques. Depending on the research direction and the candidate's interests, possible approaches may include deep learning, graph neural networks, transfer learning, explainability of machine learning, and optimization methods.
- The PhD student will have substantial freedom to develop their own research ideas within the framework of the project. The research is expected to lead to scientific publications at international conferences and in peer-reviewed journals.
- Conduct independent research on machine learning for circuit reliability analysis.
- Develop novel machine-learning methods for predicting, analyzing, or optimizing circuit reliability.
- Investigate appropriate representations of electronic circuits and design data for machine-learning models.
- Develop experimental frameworks and evaluate proposed methods using relevant circuit and EDA benchmarks.
- Publish and present research results at international conferences and in scientific journals.
- Collaborate with researchers from machine learning, circuit design, and EDA.
- Contribute to the development of publications and project activities.
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Our expectations of you
Education
- Master's degree or equivalent in Computer Science, Electrical/Electronic Engineering, Data Science, Machine Learning, or a related field.
Qualifications
- Strong theoretical and practical knowledge of machine learning and deep learning.
- Gutes Verständnis grundlegender Konzepte wie Optimierung, Generalisierung und Modellebenevaluation.
- Strong programming skills, particularly in Python and preferably PyTorch or a comparable machine-learning framework.
- Strong analytical and problem-solving abilities.
- Ability to read, understand, and critically evaluate scientific literature.
- Starkes Interesse an wissenschaftlicher Forschung und der Entwicklung neuer Methoden.
- Ability and willingness to work independently and take responsibility for your own research.
- Sehr gutes schriftliches und mündliches Englisch.
- In addition to formal qualifications, we particularly value candidates who demonstrate: Research independence, Scientific curiosity, Critical thinking, Persistence, Interdisciplinary interest, Scientific rigor, Initiative and ownership, Communication and collaboration.
Experience
- Experience in one or more of the following areas is advantageous: Electronic design automation (EDA), Circuit reliability, fault analysis, aging, or reliability modeling, RTL design, Verilog/SystemVerilog, FPGA, or ASIC design, Digital circuit design or verification, Graph neural networks and graph representation learning, Experience with EDA tools or circuit simulation, Previous research experience, for example through a Master's thesis, research project, publications, or open-source contributions.
- A strong background in machine learning is particularly valued. Previous experience in circuit design or EDA is an advantage but is not required, provided that the candidate has a strong interest in learning the relevant domain.
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What we offer
- A fully funded three-year PhD position within a DFG-funded research project.
- The opportunity to conduct research at the intersection of machine learning, EDA, and circuit reliability.
- The freedom to develop and pursue your own research ideas within the project framework.
- An interdisciplinary research environment combining machine learning and electronic design.
- Opportunities to publish research in international conferences and peer-reviewed journals.
- Opportunities to present research at international conferences and scientific workshops.
- Collaboration with academic and potentially industrial research partners.
- Access to relevant computational resources, software, and research infrastructure.
- A supportive environment for developing both scientific and technical expertise.
- 30 days holiday, special annual bonus, company pension scheme (VBL), flexible working hours, including part-time (no core hours), possibility to work up to 40% remotely according to company agreement, parent-child room as an option to work with a child in case of childcare bottlenecks, a wide range of further training opportunities in-house or during business trips, discounted company ticket with a monthly allowance of €15 for various fare zones, good transport connections, free parking at the institute, canteen with breakfast and lunch, on-site health services, company family and care guides, free confidential counselling by an external service provider for various private or professional challenges, such as balancing work and family or psychosocial emergencies, structured onboarding and actively supported integration into the institute (welcome workshop, intercultural workshop, joint leisure activities).
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Topics You Will Work On
Job Locations
About Your Employer
IHP Solutions GmbH
IHP Solutions GmbH, founded in 2015 in Frankfurt (Oder), is a subsidiary of the IHP – Leibniz Institute for Innovative Microelectronics, focusing on technology transfer in the microelectronics sector and offering a range of services.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Electronics, Automatization
PhD Position - Machine Learning for Circuit Reliability Analysis
- Location
- Frankfurt (Oder)
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
