Department of Biosystems Science and EngineeringAcronym | D-BSSE | Homepage | http://www.bsse.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | Department of Biosystems Science and Engineering | Child organizations | |
Open OpportunitiesMathematical modeling has increasingly become a pivotal tool in understanding the complex biomolecular mechanisms that underpin systems biology, as well as in the innovation of novel designs in synthetic biology. Unlike traditional disciplines in science and engineering, the field of biology presents formidable challenges that significantly complicate these modeling efforts. These challenges include but are not limited to, the inherent nonlinear nature of biological systems, their high dimensionality, the scarcity of available data, and the stochastic behaviors they may exhibit. This Master's Thesis is dedicated to the development of an advanced deep learning methodology tailored for the construction of reliable biological models. These models will be designed to accurately represent a wide spectrum of biological phenomena, ranging from dose-response relationships (steady-state input/output data) to dynamic system behaviors. The successful development of such a tool is expected to have a profound impact on multiple domains, including systems and synthetic biology, metabolic engineering, and biotechnology, among others. - Modeling and Simulation, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Optimisation, Systems Biology and Networks, Systems Theory and Control
- ETH Zurich (ETHZ), Master Thesis
| Brain organoids recapitulate important features of human neurodevelopment and allow us to study this key developmental process at unprecedented scale and resolution. In the past, single-cell genomics technologies, including single-cell RNA-sequencing (scRNA-seq), have been used to study the molecular heterogeneity of brain development in organoid models. However, these assays dissociate the tissue and thus have limited capacity to learn about emerging spatial properties like regionalization or patterning. To overcome this limitation, the Treutlein lab applies highly-multiplexed spatial transcriptomic and proteomics technologies (e.g. MERSCOPE, 4i) to jointly measure spatial organization and molecular properties of organoids. Such datasets provide a unique opportunity to study the interplay between cellular communication, gene regulation, and spatial organization. However, a key challenge remains the integration of imaging and sequencing data across replicates, conditions, and time points to learn faithful cellular representations that can be mined for regulatory interactions. Thus, the aim of this thesis will be to develop new computational methods to infer meaningful cellular representations from rich and diverse spatial datasets. - Cell Development (incl. Cell Division and Apoptosis), Knowledge Representation and Machine Learning, Modeling and Simulation, Neurosciences
- Master Thesis
| During development cells must assume different fates in a position-dependent manner. Morphogen gradients are able to encode this positional information, in order to guide tissue patterning during embryonic development. In the French flag model of patterning, morphogen concentration levels determine tissue domains of different cell fates. However, current in vitro 3D cell models fail to reproduce the patterning observed in vivo. Our aim is to generate 3D cell models which are able to reproduce patterning, thus allowing us to study morphogen gradients in diverse stages of development. - Cell Development (incl. Cell Division and Apoptosis)
- Master Thesis, Semester Project
| The student will culture neurons on a microelectrode array, and will record the electrical activity of the network and follow its evolution over time. The development of new methods for signal processing, neuron stimulation, and imaging can be included in the project depending on the experience and interests of the student. - Biology, Biomedical Engineering, Engineering/Technology Instrumentation, Neurosciences
- Bachelor Thesis, Course Project, Lab Practice, Master Thesis, Semester Project
| The student will develop an FPGA-based platform for interacting with in-vitro neuronal cultures, including real-time spike detection and neuron stimulation. The project is focused on VHDL programming, although it could include other software development and/or wet-lab tasks with neurons depending on the interests of the student. - Electrical and Electronic Engineering, Neurosciences
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| This project is about the development of integrated circuits to study neurons and neural networks, and may comprise different parts of the design including analog and/or digital microelectronics, PCB design, signal processing and programming. - Electrical and Electronic Engineering
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| The student will be involved in the development of software applications for in-vitro neural interfaces. These applications include tasks such as visualizing neural recordings, real-time signal processing, and interfacing with our CMOS-based systems. - Electrical Engineering, Engineering/Technology Instrumentation, Mathematical Software, Programming Techniques, Software Engineering
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| The Bio Engineering Lab (ETH Zurich, based in Basel) has a long tradition of pioneering densely-integrated CMOS devices capable of electrically interfacing with an in vitro neuronal systems (e.g. cultures, brain slices etc.). This position invites you to work on the fabrication methods and/or characterization of novel 3D structures that promote a strong coupling between the two heterogeneous systems, namely CMOS sensor chips and in vitro neurons. - Biomedical Engineering, Electrical and Electronic Engineering
- Master Thesis, Semester Project
| We recently developed a platform in yeast (Evolverator) that can perform in vivo evolution of binding interactions and will expand this platform to evolve peptides and proteins that bind G-protein coupled receptors (GPCRs). These receptors are important drug targets, and this platform will aim to produce agonists and antagonists for these receptors, with the eventual goal of contributing to drug discovery.
One of the key components of the platform is targeted in vivo mutagenesis of the candidate binders. The more efficient this process, the more diversified the library of binders we can screen. In the first iteration of this platform, we used the MutaT7 system[1], [2] together with an adenine and a cytosine base editor. With this system, the DNA polymerase of phage T7 is fused to the base editors. We then place a T7 promoter in front of the gene we want to target. As the gene is transcribed by the T7 polymerase, the base editors introduce mutations. While this system is quite efficient, recent publications have shown that both the type of mutations and its efficiency can be further improved[3].
The challenge is to find the most efficient set up for our specific context. There are many factors to be tested, including the placement and number of T7 promoters, new and improved base editors, as well as additional proteins that have been shown to increase mutation efficiency. The goal of this master project will be to optimize the MutaT7 system for the context of the Evolverator, with which we will first evolve ligands for the mating pathway receptor STE2 as a proof of concept. You’ll be provided with direction and initial ideas, but you will be free (and expected) to bring your own ideas as you gain experience with the method.
- Genetic Technologies: Transformation, Site-directed Mutagenesis, etc.
- ETH Zurich (ETHZ), Master Thesis
| Our lab developed transcriptional control systems (Well Tempered Controllers) in yeast that allow us to control protein levels precisely within the yeast cell[1], [2]. To build WTC systems, we design new eukaryotic promoters that can be repressed by bacterial repressors (like TetR) and induce expression using small molecules (like anhydrotetracycline). These have wide ranging applications from investigating gene-gene interactions to building complex synthetic circuits within yeast.
Currently we are building one such complex circuit in yeast that will be able to evolve functional antibodies towards G-protein coupled receptors, which are important drug targets. Although we have already developed three orthogonal WTC systems that allow orthogonal control over three separate proteins within the cell, this complex circuit requires even more orthogonal systems to achieve control over different components. The aim of this project will be to design, test, and validate more orthogonal inducer-bacterial repressor pairs that can be used to build WTC systems.
- Genetic Engineering and Enzyme Technology
- ETH Zurich (ETHZ), Master Thesis
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