Applies machine learning techniques to research problems in the life sciences with an emphasis on using computational approaches for detecting sequence patterns in a variety of contexts including cancer and metagenomic datasets. Problems typically involve the construction of computational models for phenotype prediction from genomic sequence data and other omics data. Applies computational models on new experimental data, provides measures of uncertainty, and participates in interdisciplinary discussions aimed at the design of new experiments. Reports on results of research including publishing scholarly papers in scientific journals, giving presentations at symposia, conferences, meetings, and seminars. Participates in the preparation of reports and proposals required by funding agencies to obtain and continue funding support. Position Requirements Knowledge, Skills and Experience: Bioinformatics analysis techniques and tools Fluency in python or perl Familiarity with command line Minimum bachelor’s degree in bioinformatics, cs, or biology Experience processing NGS sequence data Familiar with bacterial genomics Demonstrated work in microbiology a plus, but not required Strong knowledge of machine learning and / or statistics required Knowledge of genomics and gene structure, transcription and translation Strong analytical and problem-solving skills required Some understanding of computational algorithms to support DNA sequence alignment, small nucleotide polymorphism detection, gene expression quantification and/or small molecule (drug) structure Experience working on protected health information including electronic health records Knowledge of regulatory policies and procedures surrounding electronic protected health information required Ability to think independently and innovatively to develop exceptional technical solutions required Ability to write research publications required Attention to detail required Organizational skills required Verbal and written communication skills required Ability to work independently and as part of a team required Experience in physiology and reconciliation of genotype and experimentally determined phenotype is a plus Considerable collaborative skills, including the ability to interact well with external collaborators preferred United States citizenship is a requirement Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. RD1 Requirements: Bachelor’s and 0 years, Master’s and 0 years, or equivalent RD2 Requirements: Bachelor’s and 5+ years; Master’s and 3+ years; Doctorate and 0 years, or equivalent As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law. Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1. You will be asked to disclose any such participation in the application phase for review by Argonne’s Legal Department.
