Postdoctoral Fellow in Sepsis Research – Machine Learning for Healthcare

The Biomedical Data Science Lab investigates data-driven solutions for healthcare applications with a focus on neurological conditions such as spinal cord injury, lower back pain, neuro-degenerative disorders and neurological tumors. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer and data science. We are seeking a motivated postdoc to join this growing team and contribute to interdisciplinary research partnerships.

We are seeking a highly motivated and talented Postdoctoral Fellow to join our dynamic research team focused on advancing the understanding and treatment of sepsis, a critical condition developed by patients in intensive care units, through cutting-edge machine learning and deep learning approaches. This position offers an exceptional opportunity to work with high-dimensional and multimodal datasets collected from adult and pediatric sepsis patients to develop predictive models and novel analytical tools.

Key Responsibilities:

• Design, develop, and implement machine learning and deep learning algorithms to analyze large-scale clinical and biological datasets.
• Collaborate with clinicians, data scientists, and researchers to derive meaningful insights from complex data.
• Publish findings in high-impact journals and present at national and international conferences.
• Contribute to grant writing and proposals to secure additional funding.
• Mentor graduate and undergraduate students, as appropriate.

• PhD in Computer Science, Data Science, Machine Learning, Engineering, Biomedical Informatics, Bioengineering, or a related field
• Strong expertise in machine learning and deep learning frameworks (e.g., Keras, TensorFlow, PyTorch) and statistical modeling
• Proficient in working with foundation models and large language models (LLMs)
• Experience working with clinical datasets, including electronic health records (EHR), time series, or omics data, is highly desirable
• Proficiency in python programming 
• Demonstrated ability to work independently and as part of a multidisciplinary team
• Excellent written and verbal communication skills (Proficient in English)

Preferred Qualifications:

• Prior experience in sepsis research or critical care data analysis
• Knowledge of data preprocessing techniques for clinical data integration and harmonization
• Experience with cloud computing platforms and distributed computing tools
• Experience with developing deep learning models for time series/multimodal data
• Experience with deep learning architectures such as CNNs, LSTMs, and transformers
• A strong publication record in leading health/computer science journals or ML oriented conferences (NeurIPS, ICML, ICLR, ML4H, AAAI, CVPR, ICCV, EMNLP, ACL, etc.).

We offer a 2-year project-based contract at the BMDS lab working in the sepsis team that includes:

• Opportunities to engage with different communities bridging data science and sepsis research leading to high impact publications.
• You will be part of a highly motivated, multidisciplinary and collaborative team.
• We will support your scientific career and application for postdoctoral fellowships on your path towards scientific leadership.
• You will have flexibility to develop your own line of research within the framework of this project.
• We encourage the attendance of relevant (inter-) national conferences to increase your visibility and present the project outcomes.
• You will be involved in the supervision of junior researchers and teaching in the lab.
• Access to state-of-the-art computational resources and collaborative research networks.
• Opportunities for professional development and career advancement.