PostDoc Neuroscience Computational Biology

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Job Description:

The Population Analytics & Insights team part of Data Science and Digital Health at Johnson & Johnson Innovative Medicine is recruiting a Postdoctoral Scientist to support neuroscience research programs. This role is based in Spring House Pennsylvania.

Our team develops innovative data-driven solutions across multiple disease this position you will analyze large-scale omics data to help elucidate molecular drivers of neuropsychiatric and neurodegenerative disorders advancing AI-enabled data-driven drug discovery through modern computational biology and machine learning approaches.

Key responsibilities

You will leverage our extensive omics resources and apply state-of-the-art computational biology and machine learning methods with a primary focus on:

• Novel target identification using integrative approaches in neuropsychiatric disorders.

• Large-scale genetics association analysis.

• Proteome-wide multi-task learning for target and biomarker discovery in brain diseases

• Precision patient stratification and characterization of subtype-specific genomic signatures

You will work closely with scientists across disease genetics computational genomics AI/machine learning and the neuroscience therapeutic area to design and implement computational pipelines; analyze and interpret results; and communicate findings through internal presentations conferences and scientific publications. You will also have opportunities to collaborate with external researchers and institutions on related projects.

• Conceive develop and implement analytical solutions for high-priority scientific projects.

• Engage with scientists across Johnson & Johnson to foster collaborations and build a strong professional network.

• Analyze large-scale genetics proteomics and other omics modalities using advanced statistical and computational methods.

• Publish and present findings in top-tier journals and scientific conferences.

Qualifications:

Required:

• PhD in a quantitative field (e.g. Computational Biology Systems Biology Biostatistics Bioinformatics Statistical Genetics Computer Science or related discipline).

• Strong publication record in relevant areas.

• Hands-on experience applying machine learning methods (e.g. multi-task learning; supervised and unsupervised learning) to biological problems.

• Proficiency in R and/or Python; working knowledge of Bash and SQL; and familiarity with high-performance computing environments.

• Experience integrating multi-omics data (e.g. network-based approaches).

• Excellent written and verbal communication skills with the ability to communicate technical results to diverse stakeholders.

• Ability to work independently as well as collaboratively in a multidisciplinary team environment.

Preferred:

• Experience or domain knowledge in neuropsychiatric and/or neurodegenerative diseases.

• Experience with bulk or single-cell transcriptomics and/or high-throughput proteomics.

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The anticipated base pay range for this position is :

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