We are an interdisciplinary research group consisting of computer scientists, biologists, and physicists, working at the intersection of bio-inspired computation, intelligent behavior of simple organisms, and advanced algorithmic design. Our research aims to model, analyze, and harness distributed biological intelligence—such as collective decision-making, self-organization, and adaptive optimization—to develop novel computational methods for solving real-world industrial problems.
Our expertise spans algorithms, optimization, game theory, logic, biophysics, microbiology, and biotechnology, with a strong emphasis on translating fundamental insights into scalable computational frameworks.

Position Overview
We are seeking a Senior Liaison to serve as the intellectual and operational bridge between our research group and industrial partners. This role is central to identifying real-world problems, translating them into formal computational and mathematical frameworks, and guiding the adaptation of our bio-inspired algorithms into deployable industrial solutions.

The ideal candidate has a strong background in computer science and applied mathematics, sufficient engineering literacy, and the ability to communicate fluently with both academic researchers and industry practitioners.

Key Responsibilities:
1. Industry Engagement & Problem Discovery
Engage with industry partners across domains such as logistics, operations research, energy systems, supply chain, finance, and infrastructure.
Identify and articulate core computational challenges faced by industry (e.g., optimization under uncertainty, distributed control, resource allocation).
Extract the essential mathematical and algorithmic structure of industrial problems.

2. Translation to Computational & Scientific Language
Translate real-world industrial problems into:
Formal optimization problems
Algorithmic frameworks
Game-theoretic or multi-agent models
Map industry challenges to existing computer science and applied mathematics literature.
Identify where bio-inspired or non-classical computation provides advantages over conventional methods.

3. Research Integration
Develop a deep understanding of the group’s bio-inspired models and algorithms.
Work closely with researchers to:
Adapt theoretical models to practical constraints
Identify scalability, robustness, and implementation pathways
Help prioritize research directions based on industrial relevance and feasibility.

4. Implementation & Deployment Pathways
Advise on algorithmic implementation strategies in industrial environments.
Bridge gaps between theory and practice (e.g., data availability, computational constraints, integration with existing systems).
Collaborate with engineers and data teams when needed.

5. Strategy & Communication
Contribute to research proposals, white papers, and industry-facing technical documents.
Communicate complex ideas clearly to non-academic stakeholders.
Support partnerships, pilots, and proof-of-concept projects.

Required Qualifications:
Strong academic background in Computer Science, Applied Mathematics, Operations Research, or related fields.
Solid understanding of:
Algorithms and data structures
Optimization (continuous and/or combinatorial)
Game theory or multi-agent systems

Familiarity with:
Computational modeling
Basic concepts in machine learning
Engineering constraints and system design (at a conceptual level)
Ability to read, understand, and connect academic literature with applied problems.
Strong communication and interdisciplinary collaboration skills.
 
Preferred Qualifications
Experience working with or consulting for industry.
Familiarity with logistics, energy systems, finance, or supply chains.
Exposure to bio-inspired computation, complex systems, or unconventional computing paradigms.
Experience translating research into prototypes, pilots, or deployed solutions.
Background that combines academia and industry (e.g., applied research labs, startups).

What We Offer
A central role in shaping the real-world impact of cutting-edge interdisciplinary research.
Intellectual freedom and close collaboration with a diverse research team.
Exposure to novel computational paradigms inspired by biological intelligence.
Opportunities to influence industry practices through advanced algorithms and heuristics.