We are seeking a highly motivated and independent researcher to lead and contribute to projects in statistical genetics, computational biology, and multi-omics integration, with a focus on neurodegenerative and neuroinflammatory diseases such as Alzheimer’s disease and multiple sclerosis. The candidate will develop and apply cutting-edge analytical methods to large-scale genomic and single-cell datasets, and collaborate with multidisciplinary teams to translate genetic findings into biological insights.

In this role, typical responsibilities include:

• Demonstrated expertise in genetic association analyses using large-scale genetic data.
• Strong understanding of multi-omic data integration and its application in therapeutic target discovery.
• Experience in developing and implementing methods for data harmonization and normalization.
• Experience with cutting edge genetic analysis approaches, such as genome-wide association analysis, exome-wide association analysis, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modelling, pleiotropy analysis, meta-analysis, and the use of functional data to prioritize variants and genes of interest.
• Proven ability to independently lead and manage research projects from conception to publication.
• Develop and contribute to grant proposals to secure research funding.
• Mentor and supervise students and junior researchers, fostering their scientific development.
• Excellent communication and collaboration skills, with a track record of working effectively in interdisciplinary teams.

M.D./ D.O

We are seeking a highly motivated and independent researcher to lead and contribute to projects in statistical genetics, computational biology, and multi-omics integration, with a focus on neurodegenerative and neuroinflammatory diseases such as Alzheimer’s disease and multiple sclerosis. The candidate will develop and apply cutting-edge analytical methods to large-scale genomic and single-cell datasets, and collaborate with multidisciplinary teams to translate genetic findings into biological insights.

In this role, typical responsibilities include:

• Demonstrated expertise in genetic association analyses using large-scale genetic data.
• Strong understanding of multi-omic data integration and its application in therapeutic target discovery.
• Experience in developing and implementing methods for data harmonization and normalization.
• Experience with cutting edge genetic analysis approaches, such as genome-wide association analysis, exome-wide association analysis, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modelling, pleiotropy analysis, meta-analysis, and the use of functional data to prioritize variants and genes of interest.
• Proven ability to independently lead and manage research projects from conception to publication.
• Develop and contribute to grant proposals to secure research funding.
• Mentor and supervise students and junior researchers, fostering their scientific development.
• Excellent communication and collaboration skills, with a track record of working effectively in interdisciplinary teams.

M.D./ D.O