The Department of Translational Science & Molecular Medicine at Michigan State University’s College of Human Medicine seeks a bioinformatics scientist for appointment as an Assistant Professor. This is a renewable three-year, fixed-term position. The primary duties of the successful candidate will be to collaborate with biomedical faculty within TSMM in the analysis and interpretation of informatics data sets and provide statistical expertise. The candidate will also have time to develop an independent line of research. Candidates should be experts in the domain of bioinformatics, in particular as it relates to neuroscience, be versed in the analysis of next-generation sequencing and epigenetics data, and possess the skills to develop novel approaches and workflows as needed.
Candidates should have a strong record of publications matching their career experience to date. The candidate will be expected to participate in mentoring and instruction of students in MSU graduate training programs and work with existing faculty to broaden and enhance the vision for research at MSU. MSU offers an extremely competitive salary, benefits and start-up package.
The position requires a PhD or equivalent with a record of scholarship in bioinformatics research commensurate with experience. Dedication to mentoring students/fellows should be evident. An established track record of participating in multidisciplinary team-based collaborations is essential. Expertise and a strong track record in research related to bioinformatics, including but not limited to transcriptomics, genomics, and epigenomics. Biostatistical expertise is also required. Candidate must demonstrate expertise in running bioinformatics analysis, interpretation of the analysis and integration of the analysis with existing data. Expertise in analysis of the following platforms is required: RNA-seq, Illumina methylation arrays, and reduced representation bisulfite sequencing. Candidate must have 4+ years experience working with bioinformatics tools, including working in high performance compute cluster (HPCC) environments. Experience in R and at least one other programming or scripting language (e.g. Python, Perl, C++, bash) is required.