Job Opportunities

Project postdoctoral researcher

This is an informal overview of the job opportunities.

Please refer to the official information either on IIS HP or on JREC-IN for application (both has the same information):

(update: 19/Oct/2020) Our proposal is accepted as JST CREST Project. We added information on that.

Project overview

In laboratory for quantitative biology @IIS, UTokyo, we are working on understanding and prediction of various biological information processing by combining quantitative data analysis and mathematical modeling.

The successful candidate(s) of this opportunity are supposed to engage in the following projects:

(1) Deciphering cellular state and prediction of its dynamics by live-cell-omics technology.

The "state" of a cell is defined as the complicated pattern of intracellular gene expression and metabolic state. Although omics is a pre･dominant technique for comprehensive analysis of gene expression and metabolism at the cellular level, it is an invasive technique that cannot trace dynamics of the "state" of a single cell over time.

We aim to establish a live-cell omics technology to predict the information of omics from the Raman measurement, which is based on the correspondence between the transcriptome and Raman measurements reported by Kobayashi and Wakamoto (bioRxiv version). Live cell omics refers to a technique for estimating the state of omics in a cell from non-invasive Raman measurements of cells over time.

In particular, we are trying to address questions such as "Why do omics information and Raman measurements correspond to each other?" and "What is the underlying structure?" from the viewpoint of statistics, machine learning, and learning theory. We explore the biological mechanisms underlying such a correspondence by the mathematical modeling of self-replicating systems. We will apply the live-cell omics technology to predict drug resistance of cells.

This research will be conducted as part of the Wakamoto CREST project(2019/Oct-2024/Mar), in collaboration with Wakamoto Lab and Miyamoto Lab.

(2) Understanding and prediction of molecular recognition mechanisms in mammalian olfaction and adaptive immunity

By receiving, recognizing and processing extremely complex and diverse chemical information from the environment, an organism selects and induce complex cellular responses and differentiation pathways (signaling system), which are prominent in odor recognition (olfactory system) and antigen recognitions (immune system).

In this project, we aim to understand the mechanisms of information processing in molecular recognition by constructing a theory and data analysis method for predicting multidimensional input-output relationships. The olfactory and immune systems project distributed information acquired by a huge variety of receptors onto a high-dimensional space using random projections, from which chemical substances are classified. We are trying to understand the roles of the network structure specific to chemical substance recognition and to develop new methods for data analysis.

These theoretical predictions will be validated using simultaneous imaging of parallel signaling systems, comprehensive olfactory receptor response data, and sequence data on immune receptor repertoire.

This research will be conducted as parts of JST CREST project and of a joint research project with Ajinomoto Co.

Other information

Learn more about laboratory for quantitative biology @IIS, UTokyo from https://research.crmind.net.

Informal enquiries may be made to Dr. Tetsuya J. Kobayashi (tetsuya ### sat.t.u-tokyo.ac.jp. replace ### with @)