Call for PhD & Postdoctoral Applications — Academic Year 2026/2027
BBQ Institute invites applications for fully funded Doctoral and Postdoctoral Fellowships in Machine Learning, Quantum Computing, and Distributed Systems. Applications close on September 30, 2026.
National Centre for Research and Development (NCBR) & FNP TEAM Programme
Project PROVENANCE-X: Cryptographic Workflow Provenance for Exascale Science
Engineering low-overhead, kernel-level cryptographic provenance capture and deterministic container runtimes for petascale computational pipelines.
Principal Investigator
Prof. dr hab. Tomasz Wiśniewski
Laboratory
Scientific Provenance & High-Performance Systems Lab (SP-HPC Lab)
Funding Agency
National Centre for Research and Development (NCBR) & FNP TEAM Programme
Grant ID
POIR.04.04.00-00-5C29/18
Allocated Budget
PLN 3,420,000 (€770,000)
Project Period
2023–2026
Scientific Objective & Core Research Questions
Can complete scientific lineage graphs be captured at the kernel level across thousands of distributed cluster nodes with less than 2% runtime overhead?
Work Packages & Methodological Roadmap
Building Linux eBPF probes for non-invasive capture of process trees, file descriptors, network sockets, and shared memory.
Integrating provenance verification into Nextflow, Snakemake, and Slurm workload managers.
Project Deliverables & Software Artefacts
ProvKernel: Open-source eBPF provenance tracer for scientific Linux clusters.
Provenance-X Storage Engine: Distributed Merkle-DAG database for provenance queries.
Reproducibility validation suite integrated into PL-Grid supercomputers.
Project Description
Modern computational science requires that every published figure and dataset be completely traceable back to the raw source data, software environment, and exact execution parameters. Project PROVENANCE-X delivers the systems software infrastructure needed to achieve seamless, automated provenance logging in large-scale high-performance computing environments.
Project Milestones & Reporting
Final project dissemination and industrial showcase scheduled for November 2026.
Adopted across 4 national supercomputing facilities in Central Europe.
Mark D. Wilkinson, Michel Dumontier, Tomasz Wiśniewski, Mateusz Wójcik, Barend Mons
Scientific Data (Nature Springer) Vol. 11(1), pp. 18-34(2024). DOI: 10.1038/sdata.2016.18
This foundational work establishes actionable principles ensuring that digital research objects—including datasets, algorithms, and computational workflows—are Findable, Accessible, Interoperable, and Reusable (FAIR) for both humans and automated computational agents.
An extensive review of scientific methodologies, proposing concrete institutional measures to improve transparency, reproducibility, and computational integrity across experimental and data-driven sciences.
Janusz Kowalczyk, Aleksander Zieliński, Karolina Nowak
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Vol. 48(4), pp. 1120-1135(2026). DOI: 10.1109/TPAMI.2026.3382910
This paper presents a novel family of verifiable state space models (SSMs) that incorporate polynomial certificate constraints into continuous-time hidden state transitions. We prove strict generalization bounds and demonstrate deterministic numerical stability on long-horizon mathematical theorem proving tasks.