Duties: Carry out preparation, clean-up, and quality control of biological data, including scRNA-Seq, scATAC-Seq, Spatial transcriptomics and/or other multi-dimensional omic data modalities; Develop and maintain pipelines for bioinformatics and statistical analyses of aforementioned data types; activities to include handling raw data, evaluating outputs, optimizing parameters and summarizing findings; Collaborate with interdisciplinary teams to design experiments and analyze data from various single cell platforms; Maintain knowledge of latest bioinformatic approaches and variety sequencing technologies, especially in single-cell context; Present results at multidisciplinary project meetings; Produce output for scientific publications and co-author said publications
Requirements: Deep knowledge of bioinformatics tools and their implementation as part of pipelines, particularly for scRNA-Seq, scATAC-Seq, Spatial transcriptomics and/or other multi-dimensional omic data modalities; Demonstrated experience and understanding of genomic technologies and analysis of data generated; Analyzing and interpreting outputs to identify insights and hypotheses from data; Understanding of essential statistical methodologies required for bioinformatics analyses

Duties: The position will involve a mixture of methodological and collaborative research in biostatistics, bioinformatics, and genetics. The methodological research may include but is not limited to developing novel methods for time-to-event modeling, multivariate statistics, high-dimensional and spatial data modeling. The collaborative research may include but is not limited to software tool dissemination into clinical practice and participation in the multi-institutional efforts in studying cancer. This position will require writing statistical/biostatistical manuscripts, assisting in writing biomedical manuscripts, developing/maintaining statistical software packages, and other academic activities
Requirements: The ideal candidate should have a Ph.D. in statistics, biostatistics, or a related field. The candidate must have excellent written and verbal communication skills, the ability to engage in independent thinking, be meticulous in their attitude towards work, and be collegial as a team member. The candidate must demonstrate scholarship through at least two published first-author manuscripts

Duties: The research intern will be training and collaborating with Dr. Su's Lab within the Department of Bioinformatics and Computational Biology. The research intern will be exposed to a variety of projects that are conducted in Dr. Su's Lab, ranging from projects on performing alignment for NGS data such as RNA-Seq, DNA-Seq, ChIP-Seq, and ATAC-Seq data; implementation of R scripts to perform clustering analysis for scRNA-Seq data; or writing scientific manuscripts for publications
Requirements: Bachelor degree in Computer or related field

Duties: The primary purpose of the Associate Data Scientist is to leverage the capabilities of next-generation sequencing data to drive forward the discovery and development of novel therapeutics for cancer patients. This crucial role is centered on analyzing and interpreting intricate genetic information at the single-cell level to identify unique biomarkers and understand tumor heterogeneity. By crafting advanced computational tools and algorithms, the Associate Data Scientist will play a crucial part in accelerating scientific discoveries and contributing to the development of new therapies and diagnostics that can transform patient care and health outcomes
Requirements: Deep knowledge of bioinformatics tools and their implementation as part of pipelines, particularly for scRNA-Seq, scATAC-Seq, Spatial transcriptomics and/or other multi-dimensional omic data modalities; Demonstrated experience and understanding of genomic technologies and analysis of data generated; Analyzing and interpreting outputs to identify insights and hypotheses from data; Understanding of essential statistical methodologies required for bioinformatics analyses

Duties: The position will involve a mixture of methodological and collaborative research in biostatistics, bioinformatics, and genetics. The methodological research may include but is not limited to developing novel methods for time-to-event modeling, multivariate statistics, high-dimensional and spatial data modeling. The collaborative research may include but is not limited to software tool dissemination into clinical practice and participation in the multi-institutional efforts in studying cancer. This position will require writing statistical/biostatistical manuscripts, assisting in writing biomedical manuscripts, developing/maintaining statistical software packages, and other academic activities
Requirements: The ideal candidate should have a Ph.D. in statistics, biostatistics, or a related field. The candidate must have excellent written and verbal communication skills, the ability to engage in independent thinking, be meticulous in their attitude towards work, and be collegial as a team member. The candidate must demonstrate scholarship through at least two published first-author manuscripts

Duties: Develop and advance skills in nutritional epidemiology using data collected longitudinally from a variety of dietary assessment sources, full feeding studies, and dietary intervention trials. Develop and advance skills in clinical and molecular epidemiology, integrating clinical data with patient-reported data and biological markers in the setting of patient cohorts, and clinical and preclinical studies. With the support of a faculty mentor, independently develop new lines of research for investigation in established data, and ongoing or planned studies
Requirements: Ph.D., MD, or equivalent degree in epidemiology with significant experience and/or degree in biology and biostatistics. A clear interest in nutrition and cancer with a proven track record of publications and proficiency in writing manuscripts is required