Computational Biologist & Engineer in Genomics (Engreitz Lab, Research Data Analyst 1)

The Department of Genetics is seeking a computational biologist (Research Data Analyst 1) to join the Engreitz Laboratory to map the regulatory wiring of the human genome to discover genetic mechanisms of heart diseases.

The Engreitz Lab launched at Stanford in 2020 and is part of the Department of Genetics and the Basic Science and Engineering (BASE) Initiative of the Moore Children’s Heart Center.

The position is open, and a successful candidate could join immediately.

The experience expected from applicants, as well as additional skills and qualifications needed for this job are listed below.

Lab overview : DNA regulatory elements in the human genome, which harbor thousands of genetic risk variants for common and rare diseases and could reveal targets for therapeutics that aim to precisely tune cellular functions if only we could map the complex regulatory wiring that connects 2 million regulatory elements with 21,000 genes in thousands of cell types in the human body.

We have recently developed new approaches that could enable mapping this regulatory wiring at massive scale (see Fulco et al.

Science 2016, Fulco et al. Nature Genetics 2019, Nasser et al. Nature 2021, Bergman et al. Nature 2022). We invent new tools combining experimental and computational genomics, biochemistry, molecular biology, and human genetics to assemble regulatory maps of the human genome and uncover biological mechanisms of heart disease.

We are looking for creative and passionate people at any stage in their careers, including computational biologists and software engineers.

Candidates will train to lead and design computational projects that push the boundaries of genomic technology and reveal the functions of genetic variants associated with human diseases.

Specific projects include :

• Develop and apply predictive models for enhancer-gene regulation, including leveraging the ABC and ENCODE-rE2G framework to capture enhancer synergies and genetic variant effect sizes.
• Develop and apply methods to systematically benchmark the performance of predictive models.
• Design and analyze large-scale single-cell CRISPR screens to chart gene regulatory connections and decipher molecular mechanisms of gene regulation.

The Engreitz Laboratory is a dynamic, interdisciplinary workplace that will provide unique access to cutting-edge technologies and scientific thought, with the potential for widespread recognition of scientific contributions.

We value a diversity of values, backgrounds, and approaches to solving problems.

• The successful candidate for this position should have expertise in data analysis and software engineering, preferably with applications to high-throughput sequencing or other biological assays;
• enthusiasm for developing and applying computational approaches to learn fundamental mechanisms of gene regulation, and understand human disease;
• fluency in Unix, programming, and bioinformatics tools (Python, R, or equivalent); excellent communication, organization, and time management skills;

and be a creative, organized, motivated team player.

Duties include :

• Collaborate with experimentalists and computational biologists to develop and apply functional genomics techniques to understand gene regulation and the genetic basis of heart disease.
• Design and implement generalizable algorithms and tools for analysis of biological data, including high-throughput functional genomics assays.
• Evaluate and recommend new emerging technologies, approaches, and problems.
• Create scientifically rigorous visualizations, communications, and presentations of results.
• Contribute to generation of protocols, publications, and intellectual property.
• Maintain and organize computational infrastructure and resources.
• Other duties may also be assigned.

DESIRED QUALIFICATIONS :

Suggested : B.S. in computational biology, computer science, physics, statistics, math, molecular biology, or related field.

Motivated applicants of all levels are encouraged to apply.

• Experience in collaborative software development and relevant platforms.
• Demonstrated expertise in software engineering and / or statistical methods in data analysis, preferably with applications to high-throughput sequencing or other biological assays.
• Enthusiasm for using computational approaches to learn fundamental mechanisms of gene regulation and understand human disease.
• Excellent communication, organization, and time management skills.
• Creative, organized, motivated, team player.

EDUCATION & EXPERIENCE (REQUIRED) :

Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED) :

• Knowledge of Unix, programming, and data analysis tools (Python, R, or equivalent).
• Substantial experience with MS Office and analytical programs.
• Strong writing and analytical skills.
• Ability to prioritize workload.

CERTIFICATIONS & LICENSES :

None.

PHYSICAL REQUIREMENTS* :

• Sitting in place at computer for long periods of time with extensive keyboarding / dexterity.
• Occasionally use a telephone.
• Rarely writing by hand.
• Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

WORKING CONDITIONS :

Some work may be performed in a laboratory or field setting.

The expected pay range for this position is $66,560 to $97,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position.

The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https : / / cardinalatwork.

stanford.edu / benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees.

Specifics about the rewards package for this position may be discussed during the hiring process.

Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities.

Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form.

Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities.

Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility.

Employees may also perform other duties as assigned.

WORK STANDARDS (from JDL) :

• Interpersonal Skills : Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
• Promote Culture of Safety : Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns;

uses and promotes safe behaviors based on training and lessons learned.

Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http : / / adminguide.stanford.edu.

J-18808-Ljbffr