Data Scientist / ML Engineer

Learn the “Grammar” of Cancer Communication Networks

Location: Novi Sad, Serbia (Hybrid) or Remote
Type: Fixed term, 1 year contract with potential for extension up to 30 months
Start: After selection process, April-May 2026
Organization: NEOVIVUM TECHNOLOGIES (NEO)

Your Role

You’ll develop the machine learning pipeline that learns transformation rules governing tumor communication networks under treatment. This involves combining statistical pattern analysis, deep learning, and hybrid approaches to discover how cellular interactions evolve when drugs are applied. You’ll also build the critical integration layer connecting 4 partner institutions’ outputs (image analysis, network reconstruction, knowledge graphs) into NEO’s digital twin platform.

You’ll work in a multidisciplinary environment where biological constraints shape model architectures, computational costs influence experimental design, and clinical needs drive validation metrics. Your algorithms must remain interpretable enough to inform cancer biology research.

What You’ll Build

• Cell-cell communication network learning algorithms using statistical pattern analysis, deep learning (graph neural networks, transformers), and hybrid approaches
• ML pipelines consuming and processing partner outputs (image segmentation, network reconstruction, knowledge graphs) for proto-grammar learning algorithms.
• Scientific validation of ML predictions against experimental ground truth data to ensure ≥95% prediction accuracy
• Pipeline to consume and process network reconstruction outputs (from scRNA-seq and spatial transcriptomics)
• Ensemble modeling implementation with uncertainty quantification to provide confidence intervals on predictions

What We’re Looking For

Required:

• MSc or PhD in Computer Science, Data Science, Bioinformatics, Statistics, or related field
• Strong machine learning foundation (supervised, unsupervised, deep learning)
• Python expertise (NumPy, SciPy, pandas, scikit-learn, PyTorch or TensorFlow)
• Experience with network analysis or graph-based machine learning
• Data pipeline development skills (ETL, Luigi/Airflow, or similar orchestration)
• Scientific computing and statistical validation expertise
• Ability to work with multi-modal biological data (genomics, imaging, clinical)
• Strong collaboration and communication skills for multidisciplinary team
• Excitement about translating biological phenomena into computational models

Nice to Have:

• Experience with single-cell RNA-seq or spatial transcriptomics analysis
• Knowledge of biological networks (protein-protein interaction, cell-cell communication)
• Familiarity with knowledge graphs and semantic technologies (RDF, OWL)
• Graph neural networks or geometric deep learning experience
• Background in systems biology or computational oncology
• Test-driven development and CI/CD practices
• Previous work on EU or international research consortia

What We Offer

• Competitive compensation commensurate with experience
• Hybrid or remote work (Novi Sad (Serbia)-based hybrid preferred, full remote possible for exceptional candidates)
• Technical autonomy to design novel ML architectures for unprecedented biological problems
• International collaboration with 7 leading European research institutions (VHIR Barcelona, Politecnico di Milano, University of Bielefeld, FC.ID Lisbon, CSIC Barcelona, others)
• Multidisciplinary environment where your algorithms directly inform cancer biology discoveries and clinical validation
• Real-world impact on cancer treatment—your models will help predict patient-specific responses
• Professional development through EU research network, top-tier ML/bioinformatics conferences, publications
• Cutting-edge research at intersection of machine learning, network science, and cancer biology
• 30-month project horizon with potential for extension, commercialization, and startup opportunities
• Technical challenges that have never been solved before—genuine innovation, not incremental improvement

About NEO & Our Team

NEOVIVUM TECHNOLOGIES (NEO) is the technical lead and visionary behind CancerScan, leading both tumor modeling & validation and project exploitation. We’re a small, agile team tackling genuinely novel problems at the intersection of AI, biology, and medicine. You’ll collaborate closely with our QSP modeler, bioinformatics specialist, software engineer, and project lead. We value intellectual curiosity, rigorous validation, and iterative problem-solving. Expect to learn biology, teach ML to biologists, and question assumptions constantly.

How to Apply

Send your application to info@neovivum.com with subject line: “Data Scientist Application – [Your Name]”

Include:

1. CV highlighting relevant ML/data science experience and publications
2. Cover letter (max 1 page) explaining:
   • Your experience with biological or network data
   • Most interesting ML problem you’ve solved with unconventional data
   • Why cancer communication networks intrigue you
3. Code sample (GitHub link or attached) demonstrating ML/data pipeline work in Python

Applications reviewed on rolling basis. Position open until filled. Start ASAP.

Questions? Reach out to info@neovivum.com for informal discussion about the role, project, or team.

NEOVIVUM TECHNOLOGIES is committed to diversity and equal opportunity employment. We encourage applications from candidates of all backgrounds.