Lukas Moller
PHD Student at Caltech
Lukas Moller
PHD Student at Caltech
Pasadena, California
Overview
Work Experience
PHD Student
2023 - Current
Graduate research in Michael Elowitz's lab (SynBio): development of therapeutic protein circuits
Visiting Master's Student
2022 - 2023
Lab of Professor Feng Zhang: supporting team effort to discover, characterize, and engineer novel bacterial effector systems
Visiting Master's Student
2022 - 2023
Research in the lab of Professor Feng Zhang
Master's Student Researcher
2021 - 2022
Lab of Professor Jacob Corn: Development of Recursive Editing Recursive Editing is a method to drive high levels of HDR-repair outcomes and reduce undesired edits in CRISPR gene editing applications without cell state manipulation. Recursive Editing is based on the repeated retargeting of undesired editing byproducts. We also provide the web-tool REtarget for the automated design of Recursive Editing reagents. Our work is featured in Nature Communications: Möller, L., Aird, E. J., Schröder, M. S., Kobel, L., Kissling, L., van de Venn, L., Corn, J. E. Recursive Editing improves homology-directed repair through retargeting of undesired outcomes. Nat. Commun. 13, 4550 (2022)
Master's Student Researcher
2021 - 2022
Lab of Professor Gisbert Schneider: Machine learning-guided RNA Ligand Binding Site Prediction We developed the 3D-CNN deep-learning model RNet to predict RNA ligand binding sites. We demonstrate that protein-based pre-training improves prediction performance and helps to escape small data-regime limitations. Our work is featured in Molecular Informatics: Möller, L., Guerci, L., Isert, C., Atz, A., Schneider, G. Translating from Proteins to Ribonucleic Acids for Ligand-binding Site Detection. Mol. Inf. 41, 10 (2022)
Investment Intern
2021 - 2021
Global early-stage technology investment firm, venture capital (VC) Focus of my work: supporting early-stage biotech & AI-driven healthcare investments, biotech market analysis
Master's Student Researcher
2020 - 2020
Lab of Professor Andrew deMello: Cell Classification by Smartphone-based IFC As part of a lecture about Biomicrofluidic Engineering, I developed machine-learning-based cell classifiers using microfluidic, smartphone-based imaging flow cytometry measurements as input data.
Undergraduate Student Researcher (Bachelor Thesis)
2020 - 2020
Lab of Professor Thomas Carell: Development of caC- & hmC-Synthesis Routes I conceptualized, screened, and optimized CO-free synthesis routes toward the epigenetically relevant cytidine derivatives caC and hmC. I showed that carbon dioxide can act as an efficient carbon donor to aryl halides under mild conditions, atmospheric pressure, and without the use of metal catalysts.
Business Development Intern
2019 - 2019
Early-stage technology startup TWAICE, predictive battery analytics Focus of my work: customer archetype analysis, renewal of online marketing concept & web presence
Business Development Working Student
2018 - 2019
Focus of my work: market research to promote seed extension round, customer analysis, use case analysis, marketing Employee #8 (currently ~ 120)
Student Intern Research Department
2017 - 2017
One-week high school student internship in R&D department
Education
Doctor of Philosophy - PhD
2023 - 2028
Master of Science
2020 - 2023
Bachelor of Science
2017 - 2020
Additional Courses (Non-Degree)
2018 - 2018
A-level (German Abitur)
2009 - 2017