Openings

Position summary

We are seeking a highly motivated Computational Scientist with expertise in artificial intelligence, multi-omics data integration, and metabolic disease biology . The successful candidate will play a critical role in developing AI/ML frameworks to integrate and analyze high-dimensional biological datasets (e.g. genomics, transcriptomics, proteomics, imaging) with clinical data to identify novel mechanisms, biomarkers, and therapeutic targets in metabolic diseases such as MASLD/MASH and obesity. This position offer the candidate an opportunity to work closely with a diverse and collaborative team of computational and experimental scientists, and clinicians  on cutting-edge research at the intersection of AI and human health, and drive translational impact in metabolic diseases.

Key Responsibilities  

• Develop and implement AI/ML models to analyze and integrate multi-omics and clinical datasets related to metabolic disorders

• Collaborate with biologists and clinicians to generate testable hypotheses from integrated datasets, and contribute actively to laboratory validations and screening studies through analytical findings

• Design pipelines for preprocessing, normalization, and harmonization of heterogeneous data types

• Apply and develop novel computational methodologies to uncover disease mechanisms

• Drive biomarker discovery, patient stratification, target identification using machine learning approaches

• Build a database integrating and linking multi-dimensional clinical and multi-omics data for metabolic diseases

• Develop visualizations and dashboards to communicate complex data insights to interdisciplinary teams

• Stay up to date with emerging computational techniques and tools in systems biology and AI

• Drive high-impact scientific publications, patent filings, presentations and grant proposals

Qualifications  

• Ph.D. in Computational Biology, Bioinformatics, Computer Science, Data Science, Systems Biology, or a related field

• Strong background in programming and AI/ML (e.g., deep learning, ensemble methods, graph-based learning, agentic AI, explainable AI)

• Proficiency in programming languages such as Python and R; experience with AI/ML frameworks like TensorFlow, PyTorch, or scikit-learn

• Demonstrated experience in integrating and analysing complex multi-omics datasets (e.g., RNA-seq, WGS, proteomics, GWAS)

• Highly experienced with Unix/Linux environment and/or cloud architecture.  Solid understanding of metabolic disease biology and relevant clinical phenotypes

• Experience working with large-scale multi-dimensional datasets from biobanks, cohorts, or clinical trials

• Track record of peer-reviewed publications in computational biology or bioinformatics

• Experience in a cross-functional, collaborative environment in academia or industry

• Knowledge in data security, data standards and interoperability, and reproducible research practices

• Strong analytical and problem-solving skills, and attention to details

• Excellent oral and written communication and presentation skills

• Able to work independently and work collaboratively in a multi-disciplinary team environment

• Competent project and data management, and organizational skills

Job summary

We are seeking interns to develop computational methods, including big-data analytics, AI/ML approaches and visualization platforms, to analyze and integrate the multi-modal data (sequencing, imaging, spatial profiling, treatment response and clinical data) that can deliver translational outcomes to patients. The candidate will work with the PI and computational scientisits in the team to execute projects and carry out assigned tasks in a timely and efficient manner. He/She will report her progress on a regular basis. The intern is expected to work on any of these tasks, depending on field of study and interests.

1. Develop, implement and benchmark executable workflows for multi-omic datasets and image processing of histology images.

2. Organize and analyze in-house and publicly available datasets.

3. Develop visualization tools to visualize results in a meaningful way.

4. Curation of therapies and biomarkers, and patient clinical data.

Requirements

• Relevant fields of studies: Computational Biology, Bioinformatics, Computer Science, Biology, Mathematics, Pharmacy, Pharmaceutical Sciences, Medicine, Engineering

• The candidate should have basic programming skills (e.g. Python, R, RStudio, Jupyter Notebook, RShiny, SQL)

• Familiarity with Unix/Linux environment or cloud architecture would be an advantage

• Strong analytical and problem-solving skills

• Excellent oral and written communication and presentation skills

• Able to work independently, and as part of a team

We are actively seeking PhD students to join us in the development of novel AI/ML approaches and knowledge graphs to integrate multimodal and multiscale biomedical and research data to uncover new biological mechanisms and panel of features to predict the right precision medicine strategies.