Openings

Job summary

We are seeking an a highly motivated and innovative Bioinformatician/Data Scientist with a background in AI and Machine Learning to drive integration of diverse multi-omics and clinical data related to various diseases, including ophthalmology, cancer, metabolic and skin diseases. The successful candidate will manage large-scale multimodal data, analyze large-scale biological datasets, and contribute to the discovery of biomarkers, therapeutic targets, and understanding of complex biological systems.

Key Responsibilities

• Curate incoming large-scale multi-omics (genomics, transcriptomics, proteomics, metabolomics, lipidomics), images and clinical data

• Build data management and database solutions to manage and integrate complex datasets with compliance to data security requirements

• Implement, benchmark and execute analysis workflows for high-throughput sequencing and omics datasets to identify patterns and insights

• Visualize and build dashboards to communicate complex data outputs for scientific and

clinical applications

• Optimize algorithms for speed, accuracy, and scalability in cloud or HPC environments

• Develop AI-powered pipelines for image analysis, data integration, feature extraction, and predictive modeling

• Implement international data standards and FAIR (Findability, Accessibility, Interoperability, and Reusability) principles

• Collaborate with research teams and clinicians to translate biological and clinical questions into computational solutions

• Stay updated with advancements in AI, bioinformatics, and computational biology

Qualifications

• Bachelor’s or Master’s degree in Bioinformatics, Computational Biology, Data Science, Computer Science, Health Informatics, or related field

• Strong programming skills in Python, R, or similar languages, with experience in AI frameworks such as TensorFlow, PyTorch, Scikit-learn

• Knowledge of biological concepts, genomics, transcriptomics, or other 'omics' disciplines

• Familiarity with data visualization tools and database development

• Experience with Unix/Linux, HPC environments and cloud platforms, and large dataset processing 

Preferred Skills

• Knowledge of biological databases and data standards 

• Excellent communication, presentation and collaboration skills 

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

• Able to work independently, with competent project management and organizational skills  

• Experience in mining and analyzing public omics datasets 

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

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 develop agentic AI frameworks and intelligent chatbots to automate data analysis and interpretation, integrate high-dimensional datasets (genomics, transcriptomics, proteomics, imaging, drug screening) with clinical data, and enhance scientific collaboration. This role offers a unique opportunity to work at the interface of  AI, biomedical research, and clinical translation , collaborating with computational scientists, experimental biologists, and clinicians to uncover mechanisms, biomarkers, and therapeutic targets in metabolic diseases such as  MASLD/MASH and obesity.

Key Responsibilities

• Develop and implement AI/ML and agentic AI systems  to analyze and integrate experimental/multi-omics and clinical datasets related to metabolic diseases.

• Leverage agentic AI for automated hypothesis generation, exploratory data analysis, and prioritization of candidate mechanisms, biomarkers, and therapeutic targets.  

• Design and deploy  conversational AI chatbots and knowledge assistants to enable intuitive access to complex datasets and analytical workflows.  

• Collaborate with biologists and clinicians to refine AI-driven hypotheses into testable biological studies and validations.  

• Build scalable data pipelines for preprocessing, harmonization, and integration of

heterogeneous omics and clinical data. 

• Apply and innovate computational methodologies to uncover disease mechanisms.  

• Drive therapeutic target identification, therapeutic strategies development, and patient stratification using machine learning and AI-driven inference.  

• Build databases and interactive dashboards integrating multi-dimensional omics and clinical data with AI insights.

• Build a resource of public datasets and knowledgebase for metabolic diseases to be integrated with in-house proprietary data.

• Stay up to date with  emerging computational and agentic AI technologies  relevant to systems biology, biomedical informatics, and translational medicine.

• Collaborate with Industry partners and start-ups to accelerate agentic AI technologies development.

• Contribute to high-impact scientific publications , grant proposals, and patent filings.

Qualifications and preferred experience

• Ph.D. in  Computational Biology, Bioinformatics, Computer Science, Data Science,

Systems Biology, or a related field.

• Strong foundation in AI/ML, including deep learning, ensemble methods, graph-based learning, agentic AI, and explainable AI.

• Proven experience in  developing or integrating conversational AI/chatbots  (e.g., LLM-based assistants, RAG systems, domain-specific AI agents).

• Demonstrated experience in multi-omics data integration and analysis  (e.g., RNA-seq, WGS, proteomics, GWAS, pheWAS, drug screens).

• Proficiency in Python and R, with hands-on experience using  TensorFlow, PyTorch, or scikit-learn.

• Understanding of metabolic disease biology and relevant clinical phenotypes.

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

• Proficiency in Unix/Linux environments and cloud or HPC architecture .

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

• Strong analytical, communication, and organizational skills, with ability to work collaboratively in multidisciplinary teams.

• Knowledge of data security, FAIR principles, and reproducible research practices.

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

• 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.