positions

Task: Adaptive sensor- and context-aware learning (WP1)

Host institution: NXP

Country: Netherlands

Supervisor: Prof. Dr. F. Widdershoven [NXP]

Co-suopervisors: Dr. M. Zimmerling [TU Darstadt]; Dr. W. Houtum [NXP]

Objectives: To design, build and test a disruptive Embedded AI system with a combination of 1) a novel MCX-N microcontroller of NXP Semiconductors with embedded ML, maths, DSP and crypto accelerators, 2) a wireless network link module, and 3) a microcontroller of NXP with embedded CMOS Pixelated Capacitive Sensor (PCS) physical multi-sensing interface.

Expected Results: 1) Embedded AI boards using novel ML-enabled MCX-N microcontrollers and PCS multi-sensing; 2) Highly compressed AI models for inference and on-device learning; 3) Live demo and field-testing.

PhD enrolment: Doctoral School of TU Delft

Planned secondments: 

• TU Darmstadt (3 months, M16-M18): Context-aware embedded AI boards for zero-power embedded devices, with Prof. M. Zimmerling (KPI: joint paper)

• UNITN (4 months, M26-M29): Highly compressed models for zero-power embedded devices (KPI: joint paper)

Candidate profile: electrical engineering, embedded systems, computer science

Desirable skills/interests: embedded systems, machine learning, tinyML, AIML models, building live demonstrators from sensors, microcontrollers, radio modules, etc.

Application Deadline: February 14, 2025, AoE

Descriptions of all the 18 DC Positions

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