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Jobs Posted on the Whova Community Board of CGSI 2022

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Postdoc positions
Cornell University
Looking for highly-motivated postdocs to develop population and statistical genetics inference methods.
More details at https://aprilweilab.github.io/pages/join.html

Happy to chat more during CGSI.
Link: https://aprilweilab.github.io/pages/join.html
Postdoc/staff scientist
Scripps Research
We have open positions for postdocs and staff scientists to work on a range of research questions at the intersection of statistical machine learning and functional genomics. Find me on site in the first short course week and chat for more info.
Link: https://pejlab.org
Postdoc @ UCLA
UCLA
The Pimentel lab is looking for kind, curious, and ambitious researchers. We work on methods for functional genomics spanning from experimental design to integration of genetic variation in gene regulation.

Happy to do a joint position with someone else here — we are quite a collaborative group.

Come find Harold at the coffee breaks!
Link: pimentellab.com
Postdocs at Helmholtz Munich/UChicago/UCLA/Denmark
multiple
We're looking for multiple postdocs interested in working on depression genetics (identifying heterogeneity, improving GWAS specificity, improving PRS portability etc) using biobank, EHR and registry data. This work will be highly collaborative, between my group at Helmholtz Munich, Andy Dahl's group in Uchicago, many groups at UCLA (Jonathan Flint, Noah Zaitlen, Sriram Sankararaman etc), and Andrew Schork's group in Denmark. If interested please talk to me at first short course or second week (between the two short courses), or email/dm on whova or twitter (@caina89).
Postdoctoral Fellows in Computational Genomics -- Algorithm Development
Weill Cornell Medicine
Ideal candidates must have a Ph.D. in Computer Science, Computational Biology, Engineering or a related life sciences field with quantitative skills. Excellent computational (e.g. Algorithms, Machine Learning, Mathematics), programming (e.g. C/C++, Java or Python) and communication skills are required. Candidates with prior experience in biomolecular sequence analysis are desirable.
The successful candidate is expected to take leadership of some the exciting research questions we are actively perusing in the domains of characterizing (meta)genomes using current (and future!) sequencing technologies.
Please email your CV to "imh2003@med.cornell.edu" along with a brief description of your background and future interest. Use the subject "Postdoctoral Fellows in Computational Genomics -- Algorithm Development".
Link: https://www.imanh.org
Postdoctoral Fellows in Deep Learning
Weill Cornell Medicine
Ideal candidates must have a Ph.D. in Computer Science, Computational Biology, Engineering or a related life sciences field with quantitative skills. Excellent computational (e.g. Algorithms, Machine Learning, Mathematics), programming (e.g. C/C++, Java or Python) and communication skills are required. Candidates with prior deep learning experience are desired.
The successful candidate is expected to take leadership of some the exciting research questions we are actively perusing in the domains of deep learning imaging with applications to pathology, genomics and embryology
Please email your CV to "imh2003@med.cornell.edu" along with a brief description of your background and future interest. Use the subject "Postdoctoral Fellows in Deep Learning".
Link: http://www.imanh.org
Postdoctoral Fellow in Machine Learning for Human Genetics
UCSF & Maze Therapeutics
We are seeking a passionate and talented Postdoctoral Researcher to advance the field of applied machine learning in the context of human genetic data. This individual will conceive and execute analyses clarifying the application of natural language processing models to diverse aspects of early biological target discovery and evaluation while embedded within a collaborative academic/biotech setting. Using large-scale transformer neural networks to model the effects of protein coding variation in the human genome, the successful candidate will lead the development of novel methodology to characterize disease relevance and lay the foundations for an ultra-high throughput experimental framework.

This position is supported by the Maze Advanced Analytics Fellowship Program, which provides funding and scientific engagement to scholars interested in applied research bridging academic and industrial applications. The candidate will be jointly supervised by Dr. Vasilis Ntranos at UCSF and the Data Sciences group at Maze Therapeutics, and will work as part of a cross-functional team comprised of Data Scientists, Functional Genomic Scientists, Human Geneticists, and Computational Chemists to facilitate highly multidisciplinary early discovery research.

ABOUT THE NTRANOS LAB:

The Ntranos lab is developing computational methods at the intersection of information theory, genomics, and machine learning, with a particular focus on single-cell technologies and alternative splicing. Their research revolves around key algorithmic and statistical challenges that arise in computational biology and is highly collaborative, spanning multiple biological domains in immunology, human genetics, and cancer biology. The Ntranos lab is integrated within the broader computational research community at UCSF as part of the Dept. of Epidemiology & Biostatistics, the Diabetes Center, the Dept. of Bioengineering & Therapeutic Sciences, and the Bakar Computational Health Sciences Institute.
Link: https://opportunities.ucsf.edu/content/postdoctoral-fellow-machine-learning-human-genetics
Postdoctoral research assistant
University of Oxford
We are looking for a postdoctoral research assistant to work novel methodology to infer large-scale genealogies, study complex traits and diseases, and reconstruct human evolutionary history.
Link: https://palamaralab.github.io/
Postdoctoral fellow in machine learning and genomics at UCLA
UCLA
We have multiple openings for postdoctoral fellows in our lab. We are interested in developing statistical machine learning models and algorithms and applying them to diverse question in population and medical genomics. Projects span both foundational questions in machine learning that arise from genomic and biomedical questions and the application of ML to these questions. For more details see

www.cs.ucla.edu/~sriram/openings.html


Link: www.cs.ucla.edu/~sriram/openings.html
Postdoc in statistical genomics at UCLA
UCLA
Jingyi Jessica Li’s lab at UCLA is looking for a talented postdoc who is interested in statistical problems in single-cell and spatial omics. Interested candidates can send a CV to Jessica by email.
Link: http://jsb.ucla.edu
Postdoctoral position at UCSD
UCSD
The project aims to develop new computational tools and evaluate existing methods for using environmentally sampled genome-wide data to help ecologists and conservation biologists quantify the biodiversity in an environment. Our focus will be on non-microbial species (marine vertebrates in particular) and very precise detections of what is present in a set of samples (ideally at the species or population levels). Simply put, the project is on metagenomics of non-microbial marine species. The rationale is that the reduced cost of obtaining genome-wide data opens a path to very precise detection (beyond what meta-barcoding enables) with costs that are not dramatically higher. However, realizing this goal will require new methods and better testing of existing methods. We will tackle both challenges.

The project will involve method development, benchmarking, and biological data analysis. The best candidates will be computer scientists or bioinformaticians with an interest in working with real biological data or biologists with an interest and skills in developing and testing new computational methods.


If interested, please write directly to smiararb@ucsd.edu with Postdoc interest in the title.

The start date: as soon as possible. Preferably no later than January 2023.

Link: http://eceweb.ucsd.edu/~smirarab/2022/08/16/postdoc.html
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