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About the Role

The Applied Optimization department researches and develops mathematical methods and high-performance algorithms for the conception, planning, and operation of society's critical infrastructures. By integrating mathematical optimization, data science, and machine learning, we solve complex, large-scale challenges in areas such as energy systems, public transport, rail transport, and aviation. Our work focuses on translating theoretical foundations into scalable computational solutions that ensure the efficiency, sustainability, and resilience of these critical networks through rigorous mathematical modeling and high-performance computing. The position is located in the EnergyLab of the MODAL research campus, which develops innovative solutions in close cooperation with industrial partners to support both the strategic expansion and efficient operation of energy networks. The focus is on developing decision support tools based on mathematical optimization that ensure security of supply while minimizing investment and operating costs.

Responsibilities

Identification and utilization of underlying problem structures of energy system analysis optimization problems to enable the development of efficient solution methods.
Algorithm development & mathematical optimization: Conception, implementation, and validation of advanced mathematical optimization methods for extremely large and complex energy system models (LPs, MILPs, and MINLPs).
Interdisciplinary cooperation: Close collaboration with our technology partners (e.g., Gurobi, GAMS, Hewlett-Packard Enterprise).
Dissemination: Publication of research results in high-ranking international journals and presentation at leading conferences in the field of mathematical optimization.

Requirements

Excellent Master's degree in Mathematics, Computer Science, or related disciplines.
Sound knowledge in Algorithmic Discrete Mathematics, particularly for optimizing difficult problems.
Sound programming skills in at least one programming language, preferably C/C++ or Rust.
Experience in handling and developing optimization software.
Good knowledge of English (spoken and written); German language skills are an advantage.
Ability to cooperate and communicate effectively with partners in the joint project.

Skills

Mathematical Optimization
Algorithm Development
C/C++
Rust
Optimization Software Development

Location

Onsite

Work Type

Full-time
Limited-term contract

Experience Level

Entry-level

Education Level

Master's degree

Salary/Compensations

Entgeltgruppe 13 (TV-L)

Benefits

Active onboarding process
Family-friendly work environment with flexible working and meeting times
Varied, future-oriented, and responsible area of responsibility
Professional development opportunities and support for technical advancement
Supplementary pension plan (VBL)
30 days of annual leave
Flexible working hours (flexitime)
Remuneration based on TV-L (collective agreement for the public sector of the Länder) according to qualification and professional experience with an annual special payment
Capital city allowance of up to €150 per month, alternatively BVG-Jobticket + difference amount
Subsidized use of cafeterias and sports programs at FU Berlin due to close cooperation with Freie Universität Berlin

About the Company

The Applied Optimization department researches and develops mathematical methods and high-performance algorithms for the conception, planning, and operation of society's critical infrastructures.
The EnergyLab develops innovative solutions in close cooperation with industrial partners to support both the strategic expansion and efficient operation of energy networks.
The position is located in the EnergyLab of the MODAL research campus.

Equal Opportunity

The application of women is expressly desired, as women are underrepresented in natural sciences and information technology and ZIB strives to increase the proportion of women in this field.
Severely disabled persons will be given preference with equal qualifications.