We are seeking a motivated Computational PostDoc with expertise in human NGS data analytics and interest in single-cell analyses and/or methods development to join the Lal research group at the Cleveland Clinic, Ohio. The Lal Research Group focuses on the discovery, evaluation, and translation of biomarkers into clinical care. Specifically, the group develops computational methods that integrate large genetic, clinical, and biological data sets to improve the prediction of patient outcomes – paving the way for personalized medicine. The group’s long-term research interests involve the development of a comprehensive understanding of how alterations in the genome contribute to brain disorders.
Currently, the group Lal consists of ~12 members, including computational biologists, geneticists, clinical fellows, and software engineers, who all work as a team. The research group is also affiliated with and has labs at the Broad Institute of Harvard and MIT, US, as well as the Cologne Center for Genomics, Germany, where half of the group members are working. The postdoc is expected to present at conferences and visit her/his colleagues at the other sites annually. A positive and supportive research environment and good interpersonal relations within the team are essential for us. The Lal group works targeted oriented, and the postdoc is expected to write first author papers as well as coauthor papers from her/his colleagues. Recent completed projects can be found here: https://www.ncbi.nlm.nih.gov/pubmed/?term=Dennis+lal.
The data postdoc will interact regularly with neurologists from the Cleveland Clinic Epilepsy Center and work closely with biologists from the Dr. Angela Ting lab. The Ting lab has a strong track record in studying RNA and epigenomic biology of healthy and diseased human tissue and will perform the wet lab part of the single cell project. More information can be found here: https://www.lerner.ccf.org/gmi/ting/. Scientists from the Lal and Ting research groups will support the data interpretation of the project.
To these ends, experience in one or more of the following areas is highly desired:
- Single-cell characterization (sc/snRNA-Seq)
- Statistical genetics (GWAS/PheWAS/Fine mapping/Gene burden testing)
- Gene expression analysis (RNA-Seq, eQTL, Pathway analysis)
- Evolutionary/population genetic sequence analysis (Population structure, Homology/Conservation inference)
- Bioinformatics engineering (programming, analytical pipeline development, data visualization, high-performance computing)
- Machine learning (decision theory, clustering, network analysis, text mining)
- Develop and optimize computational pipelines to analyze human brain tissue single cell sequencing data
- Visualize, summarize, and communicate findings to project teams and other key stakeholders
- Follow relevant cutting-edge advancements in the fast-paced field of genomics, bringing developments in-house or building upon them as appropriate
- Partner with team members to improve or expand computational methods and develop best-practice, easy-to-use analytical workflows to answer common genomics questions
- PhD with experience in computational biology, statistical genetics, population genetics, bioinformatics, bioengineering, machine learning or a related field
- Required: Coding proficiency with R, Python, or a related high-performance language.
- A proven track record in the analysis, visualization, and interpretation of genomic and next-generation sequencing (NGS) data
- Demonstrated ability to work closely with project teams and/or experimental collaborators to design studies and develop analyses to answer scientific questions
- Familiarity with applying computational methods and bioinformatics tools to large- scale data including proficiency with Linux/Unix systems and high-performance computing environments
- Familiarity with relevant analytical approaches and underlying assumptions
- Detail-oriented and self-motivated approach to problem solving with excellent reasoning skills
- A team-oriented growth mindset that welcomes feedback from others and supports other team members; strong collaboration skills to work across teams and functions
- A positive attitude that enthusiastically tackles and overcomes challenges
- Strong organizational and time-management skills to prioritize needs and get things done
- Excellent presentation and communication skills, including the ability to tailor scientific content to audiences with different backgrounds
Preferred Additional Qualifications:
- Scientific understanding of the role of genetic variation in human disease, molecular biology, and cellular biology including specialized knowledge in one or more disease areas
- Coding proficiency with R, Python, or a related high-performance language.
- Strong foundation in relevant statistical principles underlying analytical approaches including some experience in methods development
- Proficiency in working in server and cloud environment
Interested applicants please submit a curriculum vitae, brief description of research interests and career goals, and contact information for three references who are familiar with the candidate’s work to Dr. Dennis Lal via email at: email@example.com