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PhDCoverLetters

Repo with PhD cover letters.

Every letter have an institute and brief description of methods and main technologies that planed to use in work.

If you find a error or incorrect plan of work - let me know.

If you disagree with something that written here - let me know.

Favorite parts

DreamCoder as it described by author - bidirectional A*, persistent states and functions instead of lisp. And NLU/knowledge bases (yep, AGI :) )

Reading competition - Q&A and getting information about known objects (as it described in definition xD). There is no need for a 20b transformer here. Grammatics as a result of statistical processing (repeated sequences).

Protein work model - 5 segments to get the form of a central fragment. Two nearest fragments with binded molecules, two farest without respect to binding (only type). There are many ions here. All can be delivered from a quantum chemistry simulator.

Atomic-scale light detector. Yes, there are quasi stationary states of electrons described by Scolkovo and IBM. So the energy of ionization can change (and several little tricks).

Myosin - make it smaller or bigger to get better muscles (mass, area and mean electrostatic potential)?

Maritime radio - there is possibility of protocols that can remove incorrect bit sequencies (that translated to electric signals and can be without some harmonics because of properties of environment) in any types of modulation. In worst scenarios we can specify a few sequencies and send data with them. Also, there is much easier to detect signals with fixed frequency in many scenarious. And many other (like in modern huawei chips, but better).

And a zero notes abouts compensation of statical moment with adjustable springs and usage of recuperation (and even mucous membranes and biological production) :).

Looks very funny, especially when you have:

Best selector (after synthesis, compared with fastest/smallets from ucdavis)

Best global optimization method (compared with standart from Matlab, or best ones with optimization of parameters hyperspace)

Best IPC technology (with generator) (compared with existed ones in linux kernel) Part 1

Best IPC technology (with generator) (compared with existed ones in linux kernel) Part 2

Machine learning with automated clustering with ensembles (3 times better than anything from SnapMl(ethz, IBM)).

And other Not yet implemented projects with strong theoretical basis

Its kinda like a overview of your portfolio of past projects

(can be PDF or website: example 1, example 2).

xD

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