PhD researcher. Emerging Demands and Innovative Practices in the Use of AI for Higher Education and Science

Constructor Knowledge Labs

ABOUT THE POSITION You are expected to conduct and lead internationally competitive research in AI-driven semantic analysis and automated reasoning-flow modeling, with applications to educational materials, scientific documents, and research authoring. Your work will focus on developing advanced methods for semantic structure extraction, conceptual and argumentative flow reconstruction, rationale-aware content generation, metacognitive prompting, and adaptive personalization. Core research contributions will include designing algorithms for concept and structure extraction, building neural/graph hybrid models for pedagogical reasoning, implementing ontology-alignment methods for cross-domain transfer, and creating human-in-the-loop optimization pipelines that incorporate expert feedback—aligning with the multi-year research roadmap (WP1–WP3) . As a postdoctoral researcher, you will take a leading role in designing experiments, shaping research directions, supervising junior researchers (including PhD students), and contributing to the development of end-to-end demonstrator systems capable of generating structured, rationale-rich, and learner-adaptive content. You will be responsible for coordinating data annotation efforts, overseeing the construction of evaluation frameworks, and driving publication-quality research outputs, including survey papers, methodology papers, and cross-domain transfer studies. Interdisciplinary collaboration is strongly encouraged, especially at the intersection of computer science, computational linguistics, cognitive science, and learning technologies, and you will have opportunities to initiate or co-lead joint projects with internal and external partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course development and supervising Bachelor’s, Master’s, and PhD theses. The university provides a supportive academic environment—including mentoring, administrative support, computational resources, and opportunities for technology transfer and industry engagement—enabling the postdoctoral researcher to establish or strengthen an internationally visible research profile. ---------------------------------------------------------------------------------------------------------------------------------- MANDATORY REQUIREMENTS * PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a closely related field. * Strong publication record in relevant top-tier venues (e.g., NeurIPS, ACL, ICML, ICLR, AIED, LAK, AAAI). * Demonstrated expertise in at least two of the following areas: * semantic parsing or structured NLP * knowledge representation, reasoning graphs, or GNNs * natural language generation, explainability, or rationale modeling * ontology alignment, cross-domain transfer, or representation learning * personalization algorithms, metacognition, or educational AI * human-in-the-loop systems or RLHF * Experience in leading research tasks, mentoring junior researchers, and coordinating multi-stage projects. * Fluency in Python and modern deep learning frameworks (PyTorch/TensorFlow). * Strong analytical, communication, and academic writing skills. * Demonstrable ability to design rigorous experimental pipelines and validation methodologies. * Responsible, independent, and proactive research personality with strong teamwork skills. * Intercultural experience and readiness to work in an international research environment. * Fluency with AI co-pilot assistants for coding and writing. * Fluency in English, the primary language of research and instruction on campus. PREFERRED QUALIFICATIONS: * Experience in developing research prototypes, evaluation benchmarks, or large-scale datasets. * Prior involvement in interdisciplinary or applied research projects. * Potential to contribute to competitive funding applications. * Experience with open-source releases or reproducible research pipelines. APPLICATION DETAILS * Starting date: March, 2026 * Contract: Full-time (100%), TV-L E13 * Work mode: Hybrid APPLICATION PACKAGE MUST INCLUDE:  * Curriculum Vitae (CV); * A detailed letter of motivation outlining research interests and career goals; * 2 recommendation letters; Applications to be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.

Constructor Knowledge Labs

Constructor University in collaboration with Constructor Knowledge Labs and Constructor Technology About the Position The research group of Dr. Sari Sadiya at Constructor Knowledge Labs (CKL), in collaboration with Constructor University (CU) and Constructor Technology (CT), invites applicants for Ph.D. student positions in Computer Science with a focus on wearable intelligence, multimodal data fusion, and edge AI. The project investigates how wearable data streams can be transformed into structured knowledge and integrated into a knowledge-grounded digital avatar that supports bi-directional collaboration in education and research. Ph.D. students will work in a highly interdisciplinary environment, combining AI/ML, edge computing, cognitive science, and human–computer interaction. In close collaboration with academia and industry, they will contribute to building privacy-preserving, real-time personalization frameworks while pursuing their doctoral dissertation. About the Program The PhD program is research-centered, emphasizing original contributions in: * Wearable data analytics and fusion methods * Biomedical data analytics * On-device processing and performance modeling * Personalization and adaptive reasoning systems * AI for Education Doctoral students will also have access to specialized courses in: * Artificial Intelligence, Machine Learning, and Edge Computing * Advanced Computational Methods and Data Science * Cognitive Science and Human-Centered Computing As part of the program, students will collaborate with Constructor Technology to gain first-hand industrial experience, contributing to real-world testbeds and prototypes. Research Focus This PhD position is part of the Wearable Intelligence Project, with two main research directions: * Data fusion of heterogeneous temporal streams * Designing algorithms to unify multimodal signals (physiological, cognitive, contextual, scheduling, and learning data). * Developing pipelines that produce structured insights powering the Agentic Personalization Engine (APE). * On-device data processing & performance modeling * Developing models balancing computation, energy, and data flows across wearable, edge, and cloud environments. * Exploring feasibility of running compact micro-LLMs directly on wearables. The overarching goal is to create scalable, ethical, and transparent personalization systems that support education and research. Funding The appointment provides full financial coverage through a dedicated fellowship, comprising: * Monthly stipend of €1,650 * Monthly research-cost allowance of €100 (Forschungskostenpauschale) * Health-insurance subsidy of €100 per month * Supplementary €603 mini-job allowance to support parallel part-time employment (optional) Constructor Knowledge Labs actively supports candidates in preparing applications for external funding — doctoral scholarships, foundations, or international mobility grants — and can provide institutional support and references Applicant Profile Mandatory requirements: * MSc degree (or equivalent) in Computer Science, AI/ML, Data Science, Cognitive Science, or related disciplines. * Strong background in AI/ML, signal processing, or edge computing. * Hands-on experience with wearable or multimodal data (e.g., heart rate, EEG, activity, sleep, GPS). * Solid mathematical and computational modeling skills. * Proficiency in academic English writing (e.g., reports, papers, theses). Preferred qualifications: * Experience with LLMs, multimodal data fusion, or agent-based AI systems. * Familiarity with privacy-preserving ML, dynamic consent, and GDPR-compliant frameworks. * Demonstrated ability to conduct independent research and collaborate across disciplines. * Interest in teaching, mentoring, and applied industrial research. Application Details * Deadline: August 31, 2026 Required documents: * Curriculum Vitae (CV); * Academic transcripts; * Letter of motivation outlining research interests and career goals; * 2 recommendation letters. Applications to be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.

Isomorphic Labs

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery.  Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you.    ABOUT ISO Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.   YOUR IMPACT  As a Senior AI Security Engineer at Isomorphic Labs, you will operate at the absolute frontier of Artificial Intelligence and Cybersecurity. Reporting directly to the CISO, your mission is to architect, secure, and future-proof our pioneering AI-first platform and autonomous agentic workflows that drive the next generation of drug discovery pipelines. In this high-impact role, you will design custom risk management frameworks tailored to the unique threat landscape of AI in life sciences, establish strict governance over critical model artifacts, and embed seamless security controls directly into distributed training and inference infrastructure. You will serve as the technical anchor bridging machine learning engineering, platform architecture, and adversarial defense. Operating in a fast-moving, high-stakes environment, you will lead AI-specific incident response and pioneer model-driven defense mechanisms to automate threat hunting and mitigation. Your work will ensure that breakthrough scientific research is paired with an uncompromising, resilient defense safeguarding invaluable intellectual property while accelerating our innovation velocity. WHAT YOU WILL DO * Adversarial Threat Modeling: Conduct cutting-edge threat modeling focused on AI/ML vulnerabilities, engineering a comprehensive risk management framework tailored to an AI-powered life sciences platform. * Model Artifacts Protection: Partner with AI teams to establish a granular inventory, classification and protection framework for ML models’ weights, code, and training data. * Agentic AI & LLM Guardrails: Design and deploy scalable guardrails, robust sandboxing, and real-time monitoring controls for our extensive LLM ecosystem, including ADK, MCP, and autonomous agentic workflows. * Collaborative Security Engineering: Partner with ML researchers and platform engineers to design and implement robust security controls across the entire ML lifecycle—from data ingestion and training pipeline integrity to inference runtime controls. * Model-Driven Incident Response: Act as the primary technical expert for AI security incidents, deploying advanced machine learning techniques to automate threat hunting, anomaly detection, and signatureless mitigation specific to LLMs. * Compliance & Governance Automation: Bridge the gap between complex AI architectures and emerging global regulations (e.g., EU AI Act) by automating risk posture monitoring and continuous compliance metrics. * AI Safety Frameworks: Pioneer the practical implementation of Isomorphic Labs' AI Safety standards, working in close coordination with Legal, Compliance, and external partners like Google DeepMind.   SKILLS AND QUALIFICATIONS  ESSENTIAL * AI/ML Engineering: Deep conceptual and practical understanding of deep learning frameworks (e.g., JAX, PyTorch, TensorFlow), large-scale cloud training or inference infrastructure, and LLM ecosystems. * Adversarial ML Mindset: Strong familiarity with AI security threat vectors (prompt injection, model inversion, data poisoning) and frameworks like OWASP Top 10 for LLMs or MITRE ATLAS. * Agentic Frameworks Security: Proven experience securing agentic frameworks (ADK, MCP), agentic first infrastructure and implementing robust agent-to-agent (A2A) identity and access controls. * Infrastructure Security: Solid proficiency in cloud platform security (GCP preferred), including container security, multi-cloud/SaaS integrations, and strict network isolation boundaries. * Pragmatic Risk Assessment: Proven ability to define and execute pragmatic mitigation strategies that balance a rigorous security posture with the high-velocity needs of a world-class scientific research organization. * Software Development & Automation: Ability to write production-grade code (Python preferred) to build custom security tooling, automate telemetry collection, or enforce policy layers. * Translational Communication: Exceptional skills in navigating ambiguity, building trusted relationships with AI researchers, and clearly translating complex machine learning risks into actionable engineering tasks for leadership. NICE TO HAVE * AI Red Teaming: Experience conducting empirical vulnerability research or executing simulated attacks against LLMs, agent networks, and core ML backends. * Regulated Environments: Prior exposure to BioTech, Pharma, and/or Deep Tech industries where data integrity, intellectual property protection, and regulatory compliance (GxP) are paramount. * Education & Background: BSc, MSc, or PhD in Computer Science, Machine Learning, Cybersecurity, or a related quantitative field. * Advanced Certifications: Relevant security or cloud credentials (e.g., OSCP, Professional Cloud Security Engineer) or specialized training in ML security. CULTURE AND VALUES We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it.  Thoughtful Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day. Brave Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less. Determined Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we. Together Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere. CREATING AN EXTRAORDINARY COMPANY We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. HYBRID WORKING It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call. Please note that when you submit an application, your data will be processed in line with our privacy policy. >> Click to view other open roles at Isomorphic Labs