We invite you to apply for a Postdoctoral Appointee position with our Data Science and Learning Division (DSL).
In this role you will:
Apply 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 complex microbial community (metagenomic) datasets.
Develop and apply computational models on new experimental data, provides measures of uncertainty, and participates in interdisciplinary discussions aimed at the design of new experiments.
Problems typically involve the construction of computational models for phenotype and/or class prediction from genomic sequence data and other omics data.
Report on results of research including publishing scholarly papers in scientific journals, giving presentations at conferences, meetings, and seminars.
Participate in the preparation of reports and proposals required by funding agencies to obtain and continue funding support.
We expect you to have:
PhD (or all but degree) in bioinformatics, computer science, microbiology or a related hard science.
Experience with machine learning, deep learning, and/or statistics required.
Strong familiarity with the command line.
Ability to code in python and/or perl or related language(s).
Demonstrated ability to publish first author papers in peer-reviewed journals.
Bioinformatics analysis techniques and tools.
Experience processing DNA sequence and other “omics” data.
Understanding of computational algorithms used in bioinformatics, such as DNA sequence alignment, small nucleotide polymorphism detection etc.
Familiarity with bacterial genomics (demonstrated work in microbiology preferred).
Strong analytical and problem-solving skills required.
Ability to think independently and innovatively to develop exceptional technical solutions required.
Strong verbal and written communication skills.
Organizational skills and attention to detail.
Ability to work independently and as part of a team required.
Collaborative skills, including the ability to interact well with external collaborators preferred.
As an equal employment opportunity and affirmative action employer, 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 is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's 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.
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