Overview:
POSITION SUMMARY:
Under the direction of a member of the faculty, the Bioinformatician is responsible for the design, development, evaluation and iterative modification of a technical infrastructure to expedite the quantitative evaluation of data resulting from studies that are laboratory based. The position will entail the establishment and maintenance of applicable in-house bioinformatics resources and interaction with individual lab members on customized research projects, as well independent projects that are the solely computational.
This is an open-rank posting (there are 4 levels of Bioinformatician) - candidates will be hired into the level commensurate with their experience.
Responsibilities:
ESSENTIAL FUNCTIONS:
Bioinformatician I:
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Establish general bioinformatics resources for day-to-day use by members of the laboratory
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In collaboration with a faculty member, generate customized programming solutions to improve user interaction with available bioinformatics resources
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Assist in the implementation of programs for microarray analysis, high-throughput sequencing data analysis, cis regulatory motif identification, and multi-genome protein motif searches
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Local establishment and customization of model organism genomic databases and tools for batch sequence analysis utilizing these resources
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Interpret and present study results in support of laboratory members
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Provide tabular and written summaries of approaches and analyses in a form suitable for inclusion in manuscripts or grant applications, as well as media for presentation at scientific meetings
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Develop and implement custom bioinformatics programming solutions in collaboration with lab as necessary
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Coordinate and collaborate with other research computing expertise at the Medical School as necessary
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Participate in conference calls and data management meetings as needed
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Perform other duties as required.
Bioinformatician II:
Duties noted above plus:
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Implement and adapt programs for microarray analysis, high-throughput sequencing data analysis, cis regulatory motif identification, and multi-genome protein motif searches.
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Independently develop, implement and maintain custom designed computational solutions relevant for ongoing lab-based projects.
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Independently develop, implement and maintain computational methods for meta-analysis of data generated in the lab as well as publicly available data.
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Independently execute a scientific computational project (e.g. a project that can result in a first author publication)
Bioinformatician III:
Duties noted above plus:
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Design and implement reusable bioinformatics analysis pipelines for processing next-generation sequencing, microarray, genomics, proteomics and chemogenomics data.
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Integrate computational methods/pipelines with high performance computing clusters.
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Collaborate closely with PIs and their lab members on research projects including defining the scope of the collaboration, researching on the scientific topics, and implementing the appropriate bioinformatics solutions that meet timelines.
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Participate in the oral presentation of all project findings and abstracts including participation in periodic project status meetings and presentation of final project deliverables.
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Develop rapid prototypes and custom scripts for one-off type of analysis requests.
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Develop novel algorithms and integrated data visualization applications when existing software packages are not available or adequate.
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Properly document the procedures used in computational analysis and provide summary report of results suitable for inclusion in manuscript and grant applications.
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Local establishment and customization of genomic, proteomics databases and provide batch analysis utilities that make use of these resources.
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Develop custom databases and web portals for managing raw and processed experimental data.
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Provide bioinformatics training and workshops for analysis pipelines and in-house developed software applications.
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Coordinate and collaborate with other bioinformaticians, biostatisticians, information technology professionals, and interdepartmental project teams.
Sr Bioinformatician:
Duties noted above plus:
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Lead the design and implementation of reusable bioinformatics analysis pipelines for processing next-generation sequencing, microarray, genomics, proteomics and chemogenomics data. Ensure pipelines meet end-user needs and project timelines
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Independently initiate and manage research collaborations. Work closely with PIs and their lab members on research projects including defining the scope of the collaboration, researching on the scientific topics, and implementing the appropriate bioinformatics solutions
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Closely follow the latest development in high-through technologies, pioneer in bioinformatics analysis on novel datasets and facilitate sharing of knowledge and best practices
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Independently develop novel algorithms and bioinformatics applications when existing software packages are not available or adequate
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Prepare scientific manuscripts and abstracts including primary authorship of bioinformatics research papers
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Organize bioinformatics training and workshops for analysis pipelines and in-house developed software applications
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Liaison with Information System department to ensure high performance computing needs for research are properly addressed
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Mentor rotation and summer internship students and junior members in the group
Qualifications:
REQUIRED QUALIFICATIONS:
Bioinformatician I:
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BS in computer science or a related discipline
- 0-1 year of related experience
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Strong background in statistical methodology, software languages and computer systems (Perl, C++, R, MySQL, etc.)
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Experience in writing basic search algorithms and the ability to generate new algorithms and programs for custom data manipulation and analysis
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Excellent communication skills, both oral and written, and interpersonal skills necessary to interact with a wide range of individuals
Bioinformatician II:
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Requirements noted for Bioinformatician I plus:
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1-3 years of related experience
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Co-authorships on peer-reviewed publications are strongly suggested but not required
Bioinformatician III:
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Requirements noted for Bioinformatician I plus:
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Master's degree in Computer Science, a related computational discipline, or equivalent experience
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1-3 years of bioinformatics-related research experience
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Proven research record such as co-authorship on peer-reviewed publications required
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Strong background in programming. Fluent in one programming language (Java or C/C++) and one scripting language (shell, Perl or Python)
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Knowledge in biostatistics packages (R or Matlab) and SQL queries are strongly suggested
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Strong communication skills, both the oral and written necessary to interact with a wide range of individuals
Sr Bioinformatician:
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Requirements noted for Bioinformatician I plus:
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Master's degree in Bioinformatics, Computer Science, or related computational discipline
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3-5 years bioinformatics-related research experience
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Knowledge in biostatistics packages (R or Matlab) and SQL queries preferred
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Highly self-motivated and demonstrated ability to manage internal and external collaborations
Additional Information:
The Dekker lab is looking for a motivated computational scientist to support and participate in ongoing research projects that explore mechanisms of chromosome folding
Our laboratory brings together experimental and computational scientists to study the principles governing how genomes fold, function, and evolve. Supported by the Howard Hughes Medical Institute, the National Institutes of Health, and the European Research Council, we are at the forefront of 3D genome research, developing and applying cutting-edge technologies to understand genome organization across scales—from individual chromatin fibers to entire chromosomes and genomes.
Our interdisciplinary approach integrates 3D genomics methods (including 3C, Hi-C, Multi-Contact 3C, Liquid Chromatin Hi-C, and SisterC), epigenomic and transcriptomic profiling, imaging techniques (light and cryo-electron microscopy), proteomics, and computational approaches spanning bioinformatics, and polymer physics–based modeling.
Over the past two decades, our work has advanced our understanding of genome architecture. We have uncovered key mechanisms of long-range gene regulation by distal enhancers, revealed how chromatin is partitioned into functional domains, discovered mechanism of chromatin loop formation, elucidated the internal organization of chromatin fibers, and established foundational models for the structure of mitotic chromosomes and the three-dimensional organization of entire genomes within the nucleus. We were also among the first to demonstrate how chromosome conformation data can enable de novo genome assembly, pioneering an approach that has since become widely adopted.
More recently, we have expanded our efforts to investigate chromosome folding across the tree of life, including the remarkable and unconventional genome organization found in dinoflagellates. By studying diverse organisms, we aim to uncover universal principles and evolutionary innovations in genome architecture.
Current research in the lab focuses on understanding how genome folding is dynamically remodeled during the cell cycle, how three-dimensional genome organization changes and possibly contributes to cellular differentiation and development, and how chromosome-folding mechanisms have evolved across species. Through the integration of innovative technologies, quantitative modeling, and biological discovery, we seek to build a predictive understanding of genome structure and function.
Key Responsibilities
Data Analysis & Visualization: Work alongside the Principal Investigator and bench scientists to process, analyze, and generate visualizations for complex biological datasets (genomics and proteomics).
Pipeline Operations: Help run, maintain, and adapt bioinformatics pipelines for modern sequencing data (short-read, long-read, 3D genomics assays, etc.) as well as mass spectrometry data.
Custom Scripting: Develop rapid, custom scripts to support one-off analysis requests from the research team.
Data Management & Tooling: Assist in organizing, documenting, and managing large-scale lab datasets to ensure data integrity and reproducibility. Develop lightweight databases and internal web portals for managing raw and processed experimental data.
Collaboration & Support: Participate in project status meetings, present findings clearly to non-computational biologists, and help document methods for publications. Provide one-on-one bioinformatics training and support for lab members.
Required Skills
Strong background in Computer Science, Biology, Physics, or a related quantitative/STEM discipline (or equivalent professional experience in the field).
Fluency in scripting languages (Python preferred) and Linux/shell scripting, with the ability to confidently navigate shared Linux computing environments.
Strong proficiency in data analysis and visualization: preferably using the scientific Python stack (NumPy, pandas, polars, matplotlib, Jupyter, etc.) and/or R and SQL.
A demonstrated portfolio of computational work, evidenced by an active GitHub profile, open-source contributions, or a proven academic research record.
Strong communication skills, both oral and written, necessary to interact effectively with a wide range of individuals across disciplines.
Preferred Qualifications
Experience with pipeline automation and workflow managers (e.g., Nextflow, Snakemake).
Familiarity with large-scale data storage formats, including both genomic (SAM/BAM/CRAM, indexing) and general tabular data (Parquet, HDF5).
Experience with Linux administration and/or cloud computing environments (AWS preferred).
Web programming experience (HTML/CSS, JS, Django) and familiarity with typed/compiled languages (C/C++, Go, Rust).
Co-authorship on peer-reviewed scientific publications.
Standard HR physical requirements (e.g., normal visual acuity, hearing, and manual dexterity) apply.
What You Will Gain:
Domain Expertise: Unmatched exposure to and training in state-of-the-art 3D genomics, epigenomics, and transcriptomic methodologies.
Cutting-Edge Data: Hands-on experience managing and analyzing massive, complex datasets, including the latest high-throughput sequencing and proteomics data.
Computational Mentorship: The opportunity to improve your skills in high-performance computing, pipeline automation, and scientific Python data analysis.
Scientific Impact: A collaborative environment where your computational work directly drives biological discovery, with strong opportunities to earn co-authorships on high-impact, peer-reviewed publications.
