Software-Design and Development

PhD - Security for Distributed Machine Learning F/M



Requisition ID: 286615
Work Area: Software-Design and Development
Expected Travel: 0 - 10%
Career Status: Student
Employment Type: Limited Full Time



SAP started in 1972 as a team of five colleagues with a desire to do something new. Together, they changed enterprise software and reinvented how business was done. Today, as a market leader in enterprise application software, we remain true to our roots. That’s why we engineer solutions to fuel innovation, foster equality and spread opportunity for our employees and customers across borders and cultures.

SAP values the entrepreneurial spirit, fostering creativity and building lasting relationships with our employees. We know that a diverse and inclusive workforce keeps us competitive and provides opportunities for all. We believe that together we can transform industries, grow economics, lift up societies and sustain our environment. Because it’s the best-run businesses that make the world run better and improve people’s lives.


Maintaining security is a constantly shifting task, and we need to respond with continuous learning and research. The portfolio of SAP Security Research contains those topics that we believe are most important for SAP’s security future. 
SAP’s vision to secure business is built on 3 ideals: Zero-Vulnerability, to harden the software by eliminating vulnerabilities, Defensible Application, to enable the software to identify and prevent attacks, and Zero-Knowledge, to make any theft of data useless through encryption.
Considering these aspects, SAP Security Research covers the following focal areas: Anonymization for Big Data, Security for Distributed Enterprise Systems, Software security analysis, Open-source analysis, Deceptive application, Applied cryptography, Quantum technology, and Machine Learning as enabler for the next generation of security.




  • With the ever-growing network of interconnected physical objects, we observe a democratization of technological trends such as Industrial IoT, Industry 4.0 or Edge Computing – and the list keeps on expanding daily– . Those materialize the convergence of IT/OT (Information/Operational Technology), with the immediate promises for early adopters:  to maximize business value of their (legacy) physical assets, and to increase their operational efficiency.
  • The industrial reality is that IoT-alike technology alone are just –brainless—piece of bare metal, flooding centralized Enterprise Systems with massive volume of unstructured and unfiltered data. But empowered with AI-based capabilities, bringing intelligence to the edge sectors, (smart) physical objects take an active role in business processes. By delegating business decisions to distributed systems, we expand the range of Enterprise Systems. And industrial applications are almost limitless: predictive maintenance in manufacturing industry moved to assembly lines machinery, traffic management in smart cities moved to video surveillance cameras, or predictive production in process industry moved to chemical pipelines.


  • The next generation of Enterprise Systems relies on the deployment of their capacities outside its centralized IT boundaries. This evolution build upon on the distribution of data and applications.  But this paradigm shift triggers several security challenges: protection of distributed data and applications.  More specifically, the deployment of AI-based capabilities, on potentially unsecure edge hardware & platforms, pave the way to numerous attacks: AI model stealing, reverse engineering, poisoning, disclosure of confidential processed input or output data, leading to uncompliancy with  data protection regulation. 


  • With this PhD position, we aim at developing an efficient and privacy-preserving approach for distributed AI-based software. This involves protection of intellectual property (IP) and the protection of inputs & outputs of such software.
  • In the last decade, this topic brought the attention of the security research community. But the proposed solutions come with major drawbacks. Leveraging on privacy-preserving computation techniques (e.g. Fully Homomorphic Encryption, Multi-Party Computation or Garbled Circuit), usually introduce an important performance bottleneck, and a lack of advanced analytics capabilities. Consequently, this has deterred their adoption by the Industry. 

The successful candidate is expected to research cutting-edge techniques addressing the above-mentioned challenges for secure distributed machine learning, including:

  • Study existing cryptographic techniques and their suitability to the protection of the underlying AI-based software (IP protection and input and output privacy)
  • Investigate novel (cryptographic) techniques for AI -based software IP safeguarding and data protection.
  • Explore innovative solutions addressing performance bottlenecks and advanced analytics mandatory for industrial use cases.


  • To achieve these goals, the candidate is expected to analyze existing methods and the challenges facing them, conceptualize and design novel solutions, implement proof-of-concept prototypes and assess these against real-world case studies. An additional important part of this position is the dissemination of research results, both inside SAP via e.g. transfer activities and patent filings, and externally via academic conference papers and presentations. 
  • The successful candidate will be integrated within our research team in Mougins, France and will be a first-class participant in our research activities, actively participating in the Mission and Goals of SAP Security Research
  • We are looking for a PhD candidate with a creative and analytical mindset, who is willing to work on cutting edge technologies in the area of Privacy and Artificial Intelligence.


  • University Level: MSc (top 10% performer in university will be favored) or engineering degree
  • Excellent programming skills (C/C++, Java, JavaScript, Python)
  • Experience in modern software development tools (Git, Docker, Debuggers)
  • Good skills in AI (Tensorflow, Deep Neural Network)
  • Knowledge of data privacy, computer security and/or big data processing
  • Fluency in English (working language). Knowledge of French, German or other language is a plus but not a prerequisite
  • Excellent oral and written communication skills
  • Willingness to travel (mainly in Europe)


  • None required



Success is what you make it. At SAP, we help you make it your own. A career at SAP can open many doors for you. If you’re searching for a company that’s dedicated to your ideas and individual growth, recognizes you for your unique contributions, fills you with a strong sense of purpose, and provides a fun, flexible and inclusive work environment – apply now.

To harness the power of innovation, SAP invests in the development of its diverse employees. We aspire to leverage the qualities and appreciate the unique competencies that each person brings to the company.

SAP is committed to the principles of Equal Employment Opportunity and to providing reasonable accommodations to applicants with physical and/or mental disabilities. If you are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team (Americas: or, APJ:, EMEA:

Successful candidates might be required to undergo a background verification with an external vendor.

Additional Locations

Requisition ID:  286615
Posted Date:  Jun 6, 2022
Work Area:  Software-Design and Development
Career Status:  Student
Employment Type:  Limited Full Time
Expected Travel:  0 - 10%

Mougins Cedex, FR, 06254

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