Open Positions
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13 positions found
PhD: Reversible Programming Languages — DC1
Develop next-generation reversible programming languages, from language design to practical integration with mainstream software ecosystems.
PhD: Concurrency and Distribution in Reversible Languages — DC2
Design reversible language features for concurrent and distributed computing, including process interaction models for shared-memory and message-passi…
PhD: Formal Verification Techniques for Reversible Languages — DC3
Advance formal verification for reversible software by combining new logical frameworks, model checking, and type-based runtime guarantees.
PhD: Reversible Sequential General-Purpose Algorithms — DC4
Create reusable methods to transform classical sequential algorithms and data structures into efficient reversible versions for real applications.
PhD: Reversible Concurrent and Distributed Algorithms — DC5
Explore how to reverse concurrent and distributed algorithms, with practical implementations for lock-free and coordination-heavy systems.
PhD: Partially Reversible Algorithms — DC6
Investigate the core trade-offs between information loss, runtime, and memory in partially reversible algorithm design.
PhD: Compilation Principles for Reversible Languages — DC7
Build compiler pipelines and optimization strategies that turn high-level reversible programs into efficient executable representations.
PhD: Design and Simulation of Adiabatic Architectures — DC8
Develop simulation tools and architecture concepts for adiabatic reversible chiplets aimed at reducing energy consumption in computing.
PhD: Design and Simulation of Reversible Neuromorphic Architectures — DC9
Research reversible neuromorphic architectures to accelerate neural workloads with a stronger focus on long-term energy efficiency.
PhD: Realisation of Energy-Efficient Custom Adiabatic Circuits — DC10
Design and prototype custom adiabatic circuits for demanding workloads such as matrix operations and AI model components.
PhD: Energy Efficiency in Blockchains — DC11
Apply reversible computing to blockchain stacks by targeting energy-heavy components such as hashing and smart-contract execution.
PhD: Energy Efficiency in Cyber-Physical Systems — DC12
Use reversible computing to improve energy profiles in cyber-physical systems, including robotics and IoT scenarios.
PhD: Energy Efficiency in Machine Learning — DC13
Rework machine-learning training components with reversible methods to cut energy usage while preserving model performance.