About Program

 

Embedded systems are at the heart of today’s digital transformation. From autonomous cars, robotics, and medical devices to smart factories and the Internet of Things, they enable intelligent, reliable, and secure technologies that shape our future.

The program Embedded Computing Systems equips students with the knowledge and skills to design, develop, and optimize next-generation embedded solutions. The program combines scientific foundations with practical expertise, covering hardware and software architectures, embedded intelligence, security, and dependability.

With hands-on projects and close ties to industry, students gain experience in real-world applications while mastering state-of-the-art design methodologies and tools. Graduates are prepared to take on leading roles in research, development, and innovation across diverse industries where embedded technologies play a decisive role.

 

Curriculum Brief

 

Program Name: Embedded Computing Systems

Program Degree: Master of Science (M.Sc) in Computer Engineering (from KIU)

Master of Science (M.Sc.) in Embedded Computing Systems (from RPTU)

Program Focus: The Master’s program in Embedded Computing Systems focuses on providing students with a deep understanding of the scientific, technological, and practical aspects of embedded and intelligent systems. Its core emphasis lies in:

• Hardware and Software Architectures – exploring state-of-the-art designs and creating new solutions for diverse application domains.

• Embedded Intelligence – integrating machine learning and AI techniques into embedded platforms.

• Design Methodologies and Tools – mastering models, languages, and computer-aided systems for design, testing, and verification.

• Dependability and Security – addressing reliability, fault tolerance, and security challenges throughout the design process.

• Applied Industrial Experience – developing practical skills through projects closely aligned with real-world industrial needs.

Through this focus, the program bridges theory and practice, preparing graduates to innovate and lead in areas such as smart devices, robotics, healthcare technologies, automotive systems, and the Internet of Things.

 

Program Goals: The Master’s Program in Embedded Computing Systems (ECSY) aims to equip students with the knowledge, skills, and expertise required to design, implement, and optimize hardware and software systems for embedded applications. The program prepares graduates for careers in industry, research, and academia by focusing on the following core goals:

G1: Develop Expertise in Embedded System Architectures

 

• Gain an in-depth understanding of modern embedded computing architectures, including microcontrollers, processors, and Systems-on-Chip (SoCs).

 

• Learn about the hardware/software co-design approach and interfacing techniques for real-time embedded applications.

G2. Master Embedded System Design and Optimization

 

• Develop the ability to analyze, design, and optimize embedded computing systems, considering performance, power efficiency, and scalability.

 

• Apply digital design methodologies and electronic design automation (EDA) tools for synthesis and verification of microelectronic circuits.

 

• Explore design methodologies for SoCs and embedded systems, ensuring efficient integration of software and hardware components.

 

G3. Understand Real-Time and Operating System Concepts

 

• Learn how real-time operating systems (RTOS) manage scheduling, memory, and power in embedded applications.

 

• Gain experience in software and firmware development for embedded platforms, ensuring responsiveness and reliability.

 

G4. Apply Advanced Verification and Testing Techniques

 

• Develop skills in formal verification, simulation, and debugging of embedded computing systems.

 

• Gain hands-on experience with industry-standard verification and validation methods, ensuring robust system performance.

 

G5. Foster Innovation in Embedded System Applications

 

• Explore real-world applications in automotive, aerospace, healthcare, industrial automation, and IoT.

 

• Learn about machine learning, AI integration, and edge computing in embedded systems.

 

• Develop solutions for smart manufacturing, robotics, and intelligent control systems.

 

G6. Provide Hands-on Experience with Cutting-Edge Technologies

 

• Work with FPGA-based prototyping, microcontroller platforms, and embedded software tools.

 

• Gain practical experience in laboratories and industry-driven projects.

 

G7. Strengthen Research and Industry Collaboration

 

• Conduct an industry-oriented or research-based Master’s thesis in collaboration with leading tech companies, research institutes, or academia.

 

• Develop scientific research skills, preparing graduates for doctoral studies or advanced R&D roles.

 

G8. Prepare for Global Career Opportunities

 

• Equip students with the interdisciplinary skills needed for careers in hardware design, embedded software development, IoT, and industrial automation.

 

• Enhance teamwork, problem-solving, and project management skills, ensuring readiness for leadership roles in embedded systems engineering.

 

Please, note: green color means that it’s for both degrees.

 

Program Modules:

• Embedded System Hardware Architectures

• System Software

• System-on-Chip (SoC) Design Methodology

 

Career Opportunities:

Program Supervisors: 

 

• ქუთაისის საერთაშორისო უნივერსიტეტი - Ia Mosashvili

• Prof. Dr.-Ing. Wolfgang Kunz

Academic Personnel

 

• Ia Mosashvili - ქუთაისის საერთაშორისო უნივერსიტეტი - Ia Mosashvili

 

Invited lecturers:

• Davit Kipshidze

• Raul Sîmpetru

• Maciej Ciesielski

• Salome Pirosmanishvili

• Konstantinos Kokkinos

• Vasili Nikolaev

 

Program Fee: 2250 GEL per year (for Georgian citizens)

4000 EURO per year (for International Students)

 

Program Structure

Semester	Course Name		Course Status	Prerequisite(s)		ECTS credits		Course Leader		Contact hours per week
I	Digital Systems		Compulsory	-		5		Ia Mosashvili (KIU)		3
	Operating Systems		Compulsory	-		5		Davit Kipshidze		3
	Digital Logic Laboratory		Compulsory	-		4		Giorgi Chachua/Ia Mosashvili		3
	Neurocomputing		Compulsory	-		5		Raul Sîmpetru		3
	Electronic Design Automation		Compulsory	-		5		Maciej Ciesielski		3
		In Total			24
I	Advanced Programming		Elective	-		3		Davit Kipshidze		2
	Machine Learning for Engineers		Elective	-		3		Salome Pirosmanishvili		2
	Research Methods and Tools		Elective	-		3		Salome Pirosmanishvili		2
The student selects two out of three elective courses						6
Total for the first semester						30

 

Semester	Course Name	Course Status	Prerequisite(s)		ECTS credits		Course Leader		Contact hours per week
II	Computer Organization	Compulsory	Digital Systems		5		Ia Mosashvili (KIU)		3
	Blockchain for Computer System	Compulsory	-		5		Davit Kipshidze		3
	IoT hardware design Lab	Compulsory	-		4		Ia Mosashvili		3
	Embedded Systems Programming I	Compulsory	-		5		Konstantinos Kokkinos		4
	VLSI design	Compulsory	Digital Systems, Electronic Design Automation		5		Maciej Ciesielski		3
	In Total			24
II	Advanced Programming	Elective	-		3		Davit Kipshidze		2
	Machine Learning for Engineers	Elective	-		3		Salome Pirosmanishvili		2
	Research Methods and Tools	Elective	-		3		Salome Pirosmanishvili		2
	Embedded Systems Programming II	Elective	-		3		Davit Kipshidze		2
	Digital Signal Processing	Elective	-		3		Raul Sîmpetru		2
The student selects two out of five elective courses					6
Total for the second semester					30

 

Semester

Course Name

Course Status

Prerequisite(s)

ECTS credits

Course Leader

Contact hours per week

III

Robotics

Compulsory

Neurocomputing, Electronic Design Automation

5

Raul Sîmpetru

3

Computer and Data Networks

Compulsory

Computer Organization

5

Vasili Nikolaev

3

Cyber-Physical Systems

Compulsory

Computer Organization

5

Vasili Nikolaev

3

In Total

15

III

Senior Design Project I

Elective

Research Methods and Tools

5

All

3

Senior Design Project II

Elective

Research Methods and Tools

5

All

3

Communication Networks

Elective

Computer Organization

5

Vasili Nikolaev

3

Microelectronics (Digital Circuits)

Elective

Electronic Design Automation

5

Davit Kipshidze

3

Deep Learning

Elective

Machine Learning for Engineers

5

Raul Sîmpetru

3

Digital Signal Processing

Elective

Digital Systems, Microelectronics

5

Raul Sîmpetru

3

The student selects three out of six elective courses

15

Total for the third semester

30

Semester

Course Name

Course Status

Prerequisite(s)

ECTS credits

Course Leader

Contact hours per week

IV

Master Thesis

Compulsory

All compulsory subjects

30

All

3

Total for the fourth semester

30

 

Admissions Requirements:

KIU:

• The right to enroll in the Master of Embedded Computing Systems Program is for bachelor’s in computer engineering, computer science, electrical engineering, mathematics or its academic equivalent;

• National Students with a degree will be admitted based on the results of the Unified Masters’ Exams and B2 English Level and Enrollment Interviews;

 

• International Students: Bachelor of computer engineering, computer science, electrical engineering, mathematics or its academic equivalent, B2 Level in English, Enrollment Interview.

 

• Questions for Enrollment Interview and criteria for evaluation student’s knowledge will be preliminary posted by KIU on the webpage at least one month before the start of Admission Interviews.

 

• It is possible to enroll in the following educational program on a mobility basis with the terms and manners established by national legislation.

RPTU:

 

Required degree

The applicant must hold at least a B.Sc. degree (or equivalent) in Computer Engineering, Electrical Engineering, Computer Science or a related program. At the time of application preliminary transcripts are accepted. Final transcripts must be provided upon enrollment.

 

The grade average of the previous study should prove high qualification of the applicant. This will normally be the case for a grade average of ‘B’ or better in terms of the ECTS grading scale.

 

English language

Applicants, who will complete one semester at RPTU or have an international professor as their supervisor/co-supervisor will be required to prove that they have sufficient fluency in English. We normally ask for IELTS 6.5 overall with at least 6.0 in each competency. This corresponds to a TOEFL iBT result with a score of about 95 out of 120. For information on accepted English language tests, please visit https://www.southampton.ac.uk/studentadmin/admissions/admissions-policies/language.page

 

The proof of English proficiency is required even when the language of instruction for the previous education was English.

 

Graduate Record Examination (GRE)

Taking the GRE test is recommended but not mandatory. The GRE code number of the University of Kaiserslautern is 7143.

 

Motivation letter

The applicant must show that he/she is well motivated for the Embedded Computing Systems programme by writing a short letter of motivation of about one page.

 

Recomendation letters

The application must be supported by two letters of recommendation from university professors or employers.