Dr. Sören Wacker
Research HPC Engineer @ TU Delft
As a Research HPC Engineer at TU Delft, I develop cutting-edge computational solutions that bridge traditional research disciplines with advanced technologies. With over 15 years of experience in High-Performance Computing (HPC), machine learning, and computational modeling, I advance large-scale scientific research across various domains.
My academic background in physics led to a PhD in computational drug design and macromolecule simulation. Having worked in Germany, Canada, and The Netherlands, I bring international expertise in computational biology, data engineering, and AI.
Projects
Explore my projects and their detailed subprojects below.
CropXR
Making crops more resilient, sustainable, and climate-adaptive through data-driven design.
Through a solid foundation of Dutch plant biology, agricultural sciences, and plant breeding, the institute adds an integrated layer of experimental research, artificial intelligence and computational modelling. The goal is to develop technology and methods to generate new crop varieties that are better adjusted to climate change and less dependent on harmful agricultural interventions.
Role: Research Engineer and Consultant
ResistanceDB
Saving lives and combating antibiotic resistance.
The Calgary Bloodstream Infection Cohort (CBSIC) is a comprehensive multi-omics dataset of more than 38,000 bloodstream infections linked to detailed patient records. It is the largest microbial dataset in the world allowing research in unprecedented richness.
Role: Data Science Lead
Selected Contributions
ProteomicsQC
Server for proteomics QC/QA pipelines
Interactive quality-control and quality-assurance pipeline server for quantitative proteomics.
Role: Lead Developer
Metabolomics Integrator
Python library and web application
The Metabolomics library for Data Scientists (ms-mint), and web-application for large-scale data processing (ms-mint-app).
Role: Lead Developer
CBSIC Dashboard
Exploratory Dashboard
The Calgary BSI Cohort dashboard allows easy access to detailed epidemiological data from CBSIC data such as patient age category, sex, organism names, acquisition type, hospital, seasonal distribution of infections, outcomes and antimicrobial resistances.
Role: Lead Developer
I’d Love To Hear From You!
Whether you have a question, feedback, or just want to share your thoughts, feel free to drop me a message below.