For Prospective Students
Join the lab
The lab welcomes prospective PhD students, postdocs, and visiting researchers across all five research areas. This page explains what we're currently recruiting for and how to apply.
By research area
Each area has its own focus and prerequisites. Read the section that matches your interest, then reach out.
Theoretical Foundations
RecruitingRecruiting for theoretical work in network structure and causal discovery, distributed optimization, thermodynamics at the small scale, and less-conservative stability analysis. Prospective students should have strong mathematical preparation.
Topics we're taking students on
- Topology reconstruction and causal discovery in dynamical networks
- Distributed ADMM and consensus in directed graphs
- Landauer bounds and thermodynamics of information erasure
- Multi-objective and structured controller synthesis
Background that helps
- Strong background in linear algebra, analysis, probability
- Prior exposure to control theory, information theory, or optimization
- Aptitude for rigorous proofs
Machine Learning & Data-Driven Methods
RecruitingRecruiting for ML with rigorous guarantees — physics-augmented deep learning, RL for security-critical control, and sample-complexity-optimal learning of dynamical systems. Emphasis on methods that carry theoretical bounds, not just empirical performance.
Topics we're taking students on
- Physics-augmented deep learning for single-molecule data
- Reinforcement learning for grid cybersecurity
- Information-theoretic sample-complexity bounds for learning DAGs
- Data-driven system identification of dynamical networks
Background that helps
- Strong ML foundations (deep learning, optimization, statistics)
- Interest in physics-informed or systems-theoretic methods
- Programming: Python + PyTorch or JAX
Sustainable Energy & Power Systems
RecruitingActively recruiting for power systems, grid-forming inverter control, cyber-secure microgrids, and distributed optimization for energy resources.
Topics we're taking students on
- Distributed control of grid-forming inverters
- Cyber-physical security for microgrids and electricity markets
- Non-intrusive load monitoring and residential grid interaction
- Consensus algorithms and distributed optimization
Background that helps
- Coursework in linear systems, control theory, or power systems
- Programming: MATLAB/Simulink; ideally Python
- Familiarity with power electronics (helpful, not required)
Nanoscience & Instrumentation
RecruitingRecruiting for probe-based nano-interrogation, high-bandwidth nanopositioning, and quantitative real-time material property measurement.
Topics we're taking students on
- Transient Force AFM and related probe-based interrogation methods
- High-bandwidth nanopositioning and modern control synthesis
- Optical tweezers with feedback-enhanced identification
- Probe-based data storage and communication-theoretic modeling
Background that helps
- Coursework in control theory, signals, or dynamics
- Interest in experimental instrumentation
- Programming: MATLAB, Python; LabVIEW or C for hardware is a plus
Single-Molecule and Cellular Biophysics
RecruitingRecruiting for single-molecule investigations of motor proteins, cargo transport, and proteins relevant to human disease — often in collaboration with the Ervasti (utrophin/dystrophin) and Sivaramakrishnan (myosin) labs.
Topics we're taking students on
- Force spectroscopy of dystrophin, utrophin, and related muscle proteins
- Molecular motor dynamics and cargo-motor interaction kinetics
- Semi-analytical models of intracellular transport
- Physics-augmented deep learning for single-molecule data
Background that helps
- Interest in biophysics and biology at the molecular scale
- Systems, controls, or estimation background
- Comfort with data analysis in Python or MATLAB
How to apply
PhD students: apply through the University of Minnesota Electrical & Computer Engineering graduate admissions program. Mention this lab and the specific research area you're interested in in your statement of purpose.
Emailing first: if you have a specific research fit in mind, a brief email to murtis@umn.edu is welcome. Include: your CV, transcripts, the research area from this page you're most interested in, and one or two lab publications from that area you've read. Do not send generic mass-emails — they're hard to reply to individually.
Postdoc candidates: email directly with CV, a research statement, and a proposed direction that connects your background to one of our five areas.
Visiting researchers: welcome. Email with your affiliation, dates, and proposed collaboration.
FAQ
- Is funding guaranteed?
- Accepted PhD students typically receive research or teaching assistantships that cover tuition and provide a stipend. Specifics are handled through the ECE graduate program.
- How long is the PhD?
- Most PhDs in the lab take four to six years, depending on the research area and prior preparation.
- Where do alumni go?
- To leading industry (Google, Apple, Amazon, Nvidia, KLA-Tencor, Cymer, Enphase, NREL, Tesla, Skyworks, GE Research, IBM Research Zurich) and faculty positions at Swansea (UK), UMN Twin-Cities, IISc Bengaluru, and CIMAT (Mexico). See Alumni.
- Do I need prior research experience?
- Preferred but not required. Strong coursework in the prerequisite areas and evidence of independent thinking matter more.