Master Theses
Network Architecture (HPC)
Data Analysis (HBP)
DAQ & Trigger (HPC, HEP)
Network Architecture (HPC)
- Routing Mechanism
- Topic: Analysis and prototyping of a routing mechanism for data transmission optimized for scientific computing
- Target: simulation, design and validation of the routing mechanism for data communication (protocol and routing mechanism) to meet the requirements of the scientific applications, including the promising field of biologically-inspired neural network learning tasks.
- The candidate should:
- be interested in data communication and interconnect;
- be interested in hardware and (or) software programming languages;
- know/be willing to learn VHDL, C, System C, Omnet++.
Data Analysis (HBP)
- Brain states
- Topic: Analysis of electrophysiological data collected from anaesthetized mice with multi-electrode surface arrays.
- Target: Determination and classification of brain states from multi-unit activity signals in healthy and pathological subjects; determination and classification of waves propagation patterns, link with the brain state and the level of anaesthesia.
- The candidate should:
- be interested in cortical activity during sleep;
- be interested in statistics and statistical analysis of experimental data;
- know/be willing to learn MATLAB and Python.
- Optical imaging
- Topic: Analysis of electrophysiological data collected from anesthetized mice with optical imaging techniques (wide-field and two-photon microscopy).
- Target: Study of waves propagation patterns, propagation speed, excitability, multi-areal connectivity; comparison with electrodes data.
- The candidate should:
- be interested in cortical activity during sleep;
- be interested in statistics and statistical analysis of experimental data;
- know/be willing to learn MATLAB and Python.
- Behaving monkeys
- Topic: Analysis of electrophysiological data collected with Utah arrays from behaving monkey performing transitive inference task.
- Target: Study of multi-areal connectivity and activation patterns; measurement of sleep-related learning performance.
- The candidate should:
- be interested in cortical activity during tasks;
- be interested in spiking and in neural encoding/decoding;
- be interested in statistics and statistical analysis of experimental data;
- know/be willing to learn MATLAB, Python and spike sorting software.
- SWAP (Slow Wave Analysis Pipeline)
- Topic:
Development and improvement of the analysis pipeline, test on experimental and simulated data. - Target: Focus on reliability, robustness, reconfigurability, portability, parallelisation, open source.
- The candidate should:
- be interested in programming, code optimization, parallelization;
- be interested in computer science and algorithms;
- know/be willing to learn MATLAB, Python + any other programming languages/tools useful for improving performance.
- Topic:
DAQ & Trigger (HPC, HEP)
- Data Transport
- Topic: Analysis and prototyping of low-latency interface towards FPGA accelerators for efficient scientific computing.
- Target: Simulation, design and validation of the hardware and software interfacing mechanism between general purpose computing node and custom hardware booster based on programmable components (FPGA) a key element of computing platforms oriented to scientific applications as well as for distributed High Energy Physics systems.
- The candidate should:
- be interested in FPGA and data communication;
- be interested in hardware and (or) software design, modeling, methodologies;
- know/be willing to learn VHDL, C, System C, Omnet++.
- AI-based online processing
- Topic: Design and prototyping of a heterogeneous distributed processing framework for AI-based online processing in High-Energy Physics.
- Target: Study the experimental requirements for an intelligent Trigger and Data Acquisition systems, identify the key aspects of an heterogeneous distributed execution platform architecture to be developed (at hardware and/or software level) and prototype them.
- The candidate should:
- be interested in Trigger and Data acquisition system
- be interested in Artificial Intelligence
- know/be willing to learn VHDL, HLS, C, System C
- DNN and Online Processing
- Topic: Study and implementation of Deep Neural Networks for online processing pipelines in High-Energy Physics with the APEIRON framework
- Target: Study, develop and prototype DNN models within a HW/SW co-design loop between definition of processing, specification of the execution platform and mapping among them through performance evaluation.
- The candidate should:
- be interested in Trigger and Data acquisition system
- be interested in Deep, Neural Network
- know/be willing to learn C, HLS